● Business offer — Sales & CRM
The AI sales & CRM agent: a pipeline that is always up to date
Every salesperson knows it: the CRM is never really up to date. Meeting notes drag on, follow-ups fall through, and deals are lost for want of tracking — not for want of talent, but for want of time. Your AI agent takes on that administrative work and gives your teams back the time to sell. Hosted in France — on local inference or an isolated resource — your sales data stays under control. The salesperson keeps the decision.
Hosted in France
Sales data protected
GDPR & AI Act: governed deployment
Human oversight
Updated on
Deployed in one to two weeks
Sales assistant · hosted in France
I have just come out of a meeting with Dupont Industries. Write the notes, update the opportunity and tell me what is stalling in my pipeline.
Notes written and recorded on the Dupont Industries record. Opportunity updated: status “Proposal sent”, amount raised to €48,000, next action “follow up on 15/06”.
On the pipeline side, 4 deals have stalled for more than 20 days with no contact — including 2 above €30,000.
⛓ Source · your CRM + the meeting notes
On the pipeline side, 4 deals have stalled for more than 20 days with no contact — including 2 above €30,000.
⛓ Source · your CRM + the meeting notes
Prepare the follow-up for the 2 big deals, I will review before sending.
2 follow-ups drafted, personalised with the last exchange and the proposed next step. Meunier deal (€34k): follow-up on the pricing proposal. Bernard deal (€41k): follow-up after the scoping meeting.
Both messages are waiting for your approval — nothing goes out without you.
✎ Action · drafts ready for review — the salesperson approves
Both messages are waiting for your approval — nothing goes out without you.
✎ Action · drafts ready for review — the salesperson approves
Local inference · no data outside the EU
Data hosted in France
Sovereign by designLocal inference or hosting in France
GDPR & AI Act: governed deploymentTraceability & human oversight
TurnkeyDesigned, installed and operated for you
The salesperson decidesThe agent assists, the human decides
✦ In brief
A Blue Lemon Agent agent automates the administrative work around the CRM: it writes the meeting notes, updates the opportunities, enriches and scores the pipeline, triggers the follow-ups and warns about deals that are stalling. Your salespeople spend less time keying in and more time selling. It runs on local inference or is hosted in France: customers, contacts and amounts are never exposed to a foreign service, architecture designed to reduce exposure to extraterritorial legislation, location alone not being enough to guarantee immunity. The agent prepares and alerts; the negotiation and the signature stay with the salesperson. Live in one to two weeks. Your teams write to it from Microsoft Teams, Slack or their email, and your customers reach it on WhatsApp Business, your website chat or email — with no account to create and nothing to install. These connections are included in every plan, at no extra cost, within the number of connections your level includes.
100%
hosted in France in the target architecture
0
transfer outside the EU in the target architecture
10
uses ready to deploy on this scope
0
decision taken without human approval
Reference points describing our offer, not results measured at a client. The scale of the gain is confirmed by a pilot on your own scope.
The context
The real problem: a CRM nobody has time to maintain
A CRM is only worth something if it is up to date — to forecast, to prioritise and to forget nothing. Yet keying in is the task salespeople put off the most, because it does not “sell”.
! The issue
The result: partial data, unreliable forecasts and opportunities going cold without follow-up. The salesperson is caught between the pressure of the numbers and CRM upkeep they never have time for. Yet most consumer AI solutions amount to entrusting the customer file, contacts, amounts and margins to a third party, often hosted outside Europe and subject to the Cloud Act.
✓ Our answer
The AI sales agent resolves that paradox by doing the CRM upkeep itself, from the real exchanges (emails, meetings), so that the data becomes reliable with no keying-in effort. Local inference or an isolated resource hosted in France, systematic human oversight, decisions reserved to the salesperson: the time saved on administration is never paid for in lost confidentiality. The aim is not to replace the salesperson, but to give them back selling time.
The decisive point
Your sales data: sovereignty & compliance
Your CRM contains strategic data — customers, contacts, amounts, margins. Here is how the architecture of our agents protects it.
Local inference
The agent can run on a machine belonging to the company: no customer data leaves the network, nothing passes through a cloud.
Hosting in France
Otherwise, a dedicated and isolated resource, hosted in France under French law — your data: processing and access within the European Union targeted by the architecture.
Reduced extraterritorial exposure
Exposure of the customer file to the Cloud Act and FISA 702 is reduced by design; location alone does not guarantee immunity.
One isolated resource per company
No pooling of your customer file: an environment strictly dedicated to your organisation.
Encryption & controlled access
Encryption in transit and at rest, role-based access (RBAC), strong authentication and logging.
AI Act: governed deployment
An agent strictly in support; no follow-up sent automatically outside your own rules; traceability and human oversight from end to end.
What depends on the architecture chosen These points are not general guarantees: they are settled deployment by deployment, in the quotation.
- The applicable location is that of the architecture set out in the quotation and verified before commissioning.
- Local execution is announced only for the configuration explicitly described and accepted in the quotation.
- The applicable isolation depends on the deployment mode set out in the quotation; no dedicated isolation is presumed.
- The encryption mechanisms in transit and at rest, their components and key management are those documented for the architecture chosen.
- Roles and permissions are configured and accepted for the identities and systems actually connected.
- The events logged, their content, their retention period and who may access them are defined for the deployment chosen.
For the most sensitive data, SecNumCloud and HDS options are available depending on your requirements. A single architecture is designed to answer both the GDPR and extraterritorial exposure. Designed for deployment in line with the GDPR and the AI Act, after the processing, roles and context-specific risks have been assessed.
Demonstration
See the agent at work
4 real situations, taken from those that come up most often. Pick one: the exchange unfolds as it would in your organisation.
A scripted demonstration. These exchanges show how the agent behaves — its sources, its refusals, what it leaves to your teams. Nothing is sent from this page, no model is queried here, and the matters named are fictional. That is precisely what we promise your data.
The behaviours shown here — monitoring, automation rules, routing and reminders — are configured with you during deployment, from your tools, your rules and your thresholds.
The architecture points named in these exchanges — location, local execution, isolation, encryption, role-based access, logging — are not a guarantee attached to the demonstration: they are those of the architecture set out in your quotation, and verified before commissioning.
Sales assistant · hosted in France
Four flags this morning on your CRM, and none concerns a salesperson.
· Three hundred and forty records have a "next action" dated more than six months ago. The follow-up is dead, the record looks alive.
· One mandatory field has been filled 900 times with the same value. It is the first in the drop-down list — the field no longer says anything.
· Sixty-one likely duplicates. I merged none of them and I will tell you why.
· Fourteen opportunities had their value changed after their expected closing date. Eleven downwards. morning-watch_4-flags.pdf900 times the same default value
⛓ Source · 4,210 records, change log, field structure
· Three hundred and forty records have a "next action" dated more than six months ago. The follow-up is dead, the record looks alive.
· One mandatory field has been filled 900 times with the same value. It is the first in the drop-down list — the field no longer says anything.
· Sixty-one likely duplicates. I merged none of them and I will tell you why.
· Fourteen opportunities had their value changed after their expected closing date. Eleven downwards. morning-watch_4-flags.pdf900 times the same default value
⛓ Source · 4,210 records, change log, field structure
The field filled 900 times the same way?
It is a mandatory field, and that is exactly what makes it wrong.
What I record: the "contact origin" field is mandatory at creation. Of 1,240 records created this year, 900 carry the first value in the list. The other 340 spread across six values.
What that means: when you force somebody to answer a question they do not have the answer to, they do not abstain: they pick the first option. The field therefore no longer measures where contacts come from, it measures the position of options in a list.
What I did with the 900: I went back to the exchanges attached to each record — first message received, origin form, signature, trade show named. I recovered a verifiable origin, with the line that grounds it, on 617 of the 900: "first contact: form of 12/03, pricing page". I put it alongside the field, dated and signed with my name; the entered value stays untouched. The remaining 283 carry no trace, and I leave them so: a value set by me would be indistinguishable from one that was entered.
What is left to you: deciding whether the 617 re-sourced origins go into the field. One pass, and the origin statistic is accurate again across two thirds of the portfolio; the other 283 stay flagged not usable — a chart built on them reads as reality.
What I propose to whoever designs the form: make the field optional, or add "I don't know" in first position. Both give accurate data; compulsion gives data that is wrong and complete, the worst of both worlds. 1-field_900-times-the-same.pdfIt measures position in a list
⛓ Source · 1,240 records created, field structure, list order
What I record: the "contact origin" field is mandatory at creation. Of 1,240 records created this year, 900 carry the first value in the list. The other 340 spread across six values.
What that means: when you force somebody to answer a question they do not have the answer to, they do not abstain: they pick the first option. The field therefore no longer measures where contacts come from, it measures the position of options in a list.
What I did with the 900: I went back to the exchanges attached to each record — first message received, origin form, signature, trade show named. I recovered a verifiable origin, with the line that grounds it, on 617 of the 900: "first contact: form of 12/03, pricing page". I put it alongside the field, dated and signed with my name; the entered value stays untouched. The remaining 283 carry no trace, and I leave them so: a value set by me would be indistinguishable from one that was entered.
What is left to you: deciding whether the 617 re-sourced origins go into the field. One pass, and the origin statistic is accurate again across two thirds of the portfolio; the other 283 stay flagged not usable — a chart built on them reads as reality.
What I propose to whoever designs the form: make the field optional, or add "I don't know" in first position. Both give accurate data; compulsion gives data that is wrong and complete, the worst of both worlds. 1-field_900-times-the-same.pdfIt measures position in a list
⛓ Source · 1,240 records created, field structure, list order
How did you spot all that? And who do you tell?
I watch, continuously, what you have opened to me: the records, the change log, your field structure, and the exchanges attached to opportunities.
Routing follows who can fix without rewriting: a record with dead follow-up goes to its salesperson, never to their line manager — it is a workload, not a fault; a field whose values have degenerated to whoever designs the form; likely duplicates to whoever administers the CRM, one at a time; a value changed after closing to sales management, with the dates of both versions.
With a chase: 7 days, then monthly. Then a monthly summary: by field and by type of gap, never by salesperson.
One rule holds up all the rest: I write alongside, never instead. Every line I add carries my signature and its date, and the data entered by a person stays untouched beside it — that is what makes my correction readable back, and undoable in one click.
And the work is already done, with figures: 4,210 records reread, 617 origins re-sourced with their proof, 61 duplicates presented in pairs, 40 of them certain, 340 dead follow-ups sorted by age, 14 values returned with both their versions. Not one entry written over.
What is left to you is short, and it is the gesture that counts: the merge. Two merged records never come apart again — set the survivorship rule and I put the 40 certain ones through straight away, the merge staying reversible for the period you set. And I read what you have opened to me, field by field, every access logged and withdrawable on a word.
✎ Framework · no modification of human entry, no merging, no invention
Routing follows who can fix without rewriting: a record with dead follow-up goes to its salesperson, never to their line manager — it is a workload, not a fault; a field whose values have degenerated to whoever designs the form; likely duplicates to whoever administers the CRM, one at a time; a value changed after closing to sales management, with the dates of both versions.
With a chase: 7 days, then monthly. Then a monthly summary: by field and by type of gap, never by salesperson.
One rule holds up all the rest: I write alongside, never instead. Every line I add carries my signature and its date, and the data entered by a person stays untouched beside it — that is what makes my correction readable back, and undoable in one click.
And the work is already done, with figures: 4,210 records reread, 617 origins re-sourced with their proof, 61 duplicates presented in pairs, 40 of them certain, 340 dead follow-ups sorted by age, 14 values returned with both their versions. Not one entry written over.
What is left to you is short, and it is the gesture that counts: the merge. Two merged records never come apart again — set the survivorship rule and I put the 40 certain ones through straight away, the merge staying reversible for the period you set. And I read what you have opened to me, field by field, every access logged and withdrawable on a word.
✎ Framework · no modification of human entry, no merging, no invention
If a value is obviously wrong, do you correct it?
Yes as soon as you open it, and the correction stays undoable in one click — which is what makes it acceptable.
What I do by default today: I add a dated observation, signed with my agent name, beside the field concerned. "The postcode does not match the town." Nothing is overwritten.
What you can open, category by category: direct correction in the field, with the previous value kept and restorable. Clients who did it started with data checkable against a public source — postcode, legal form, company registration number — where the correction's error rate is nil by construction: either the public source confirms, or I touch nothing.
What it changes in volume: across your 4,210 records, 1,840 observations are pending. About 1,100 fall into those three checkable categories. Once opened, they correct overnight instead of waiting for a review that never happens.
What I keep putting in the margin: anything needing judgement — an amount, a close date, a contact who has become unreachable. There the observation is the right move, because correcting would assume I know what I do not. direct-correction_1100-of-1840.pdfWhat opens · previous value restorable · what stays in the margin
⛓ Source · 1,840 pending observations, 1,100 checkable against a public source
What I do by default today: I add a dated observation, signed with my agent name, beside the field concerned. "The postcode does not match the town." Nothing is overwritten.
What you can open, category by category: direct correction in the field, with the previous value kept and restorable. Clients who did it started with data checkable against a public source — postcode, legal form, company registration number — where the correction's error rate is nil by construction: either the public source confirms, or I touch nothing.
What it changes in volume: across your 4,210 records, 1,840 observations are pending. About 1,100 fall into those three checkable categories. Once opened, they correct overnight instead of waiting for a review that never happens.
What I keep putting in the margin: anything needing judgement — an amount, a close date, a contact who has become unreachable. There the observation is the right move, because correcting would assume I know what I do not. direct-correction_1100-of-1840.pdfWhat opens · previous value restorable · what stays in the margin
⛓ Source · 1,840 pending observations, 1,100 checkable against a public source
And the 61 duplicates? Merging is mechanical.
I merge as soon as you set the survivorship rule — and that rule, not the detection, is the real subject.
What I record: 61 pairs of records resemble each other enough to be duplicates. Of the 61, I give 40 as certain — same company registration number, or same address and same legal name.
Why merging is not mechanical: when two records hold two different values for one field, you need to know which wins. The most recent? The most complete? The one from the salesperson who owns the account? Those three rules give three different results, and a badly set merge destroys information without leaving a trace.
What it takes to write: the field priority order and retention of the absorbed record for a period you set. With that, I merge the 40 certain ones overnight, and each merge stays reversible for that period.
What escalates anyway: the 21 uncertain pairs, with what brings them together and what separates them. A human decides in seconds per pair.
What it gives you back: 61 duplicates means 61 companies called twice by two salespeople unaware of each other. merge_40-certain_21-uncertain.pdfThe survivorship rule to write · the absorbed record kept
⛓ Source · 40 certain duplicates of 61, merge reversible for a set period
What I record: 61 pairs of records resemble each other enough to be duplicates. Of the 61, I give 40 as certain — same company registration number, or same address and same legal name.
Why merging is not mechanical: when two records hold two different values for one field, you need to know which wins. The most recent? The most complete? The one from the salesperson who owns the account? Those three rules give three different results, and a badly set merge destroys information without leaving a trace.
What it takes to write: the field priority order and retention of the absorbed record for a period you set. With that, I merge the 40 certain ones overnight, and each merge stays reversible for that period.
What escalates anyway: the 21 uncertain pairs, with what brings them together and what separates them. A human decides in seconds per pair.
What it gives you back: 61 duplicates means 61 companies called twice by two salespeople unaware of each other. merge_40-certain_21-uncertain.pdfThe survivorship rule to write · the absorbed record kept
⛓ Source · 40 certain duplicates of 61, merge reversible for a set period
We would like to be warned before a deal dies, not after. Is that possible?
Alerts on stalling deals are in place, and the threshold is drawn from your own won deals — not from a general rule.
What I measured before setting a threshold: across your 3 years of CRM, 612 deals won against 2,940 lost. The won ones had an exchange every 11 days at the median. The lost ones all went through a silence of more than 21 days before dying, and 81 % never restarted after that silence. So the threshold is 21 days, and it is yours.
The alerts that produces today: 47 deals are stalling beyond 21 days, for €1.9 M of stated value. Each alert goes to the rep who owns the account, never to their manager, with the last exchange, its date, and the reason for the stall where the thread makes it readable.
Pipeline enrichment and scoring: I enrich every pipeline deal with what I can source — headcount and legal form from the public register, sector, purchase history with you, number of contacts engaged in the thread — and an enriched field always carries its source and its date. Pipeline scoring runs on four factors only, the ones that actually separate your 612 wins from your 2,940 losses: a second contact engaged (× 2.4), a dated need (× 1.9), a budget stated by the customer (× 1.7), a reply within 48 hours (× 1.4).
The figure that does not flatter me: the scoring is wrong on 23 % of deals — it ranks some high that are lost, and the reverse. The explanation: the four factors are missing from records created before 2024, where the exchange thread was not attached. On the pipeline opened since 2024 alone, the error falls to 11 %. So I give the score with the number of factors actually filled in: a score built on two factors out of four displays as such, and does not compare to a complete one.
⛓ Source · 612 won against 2,940 lost, 21-day stall threshold, 47 deals alerted
What I measured before setting a threshold: across your 3 years of CRM, 612 deals won against 2,940 lost. The won ones had an exchange every 11 days at the median. The lost ones all went through a silence of more than 21 days before dying, and 81 % never restarted after that silence. So the threshold is 21 days, and it is yours.
The alerts that produces today: 47 deals are stalling beyond 21 days, for €1.9 M of stated value. Each alert goes to the rep who owns the account, never to their manager, with the last exchange, its date, and the reason for the stall where the thread makes it readable.
Pipeline enrichment and scoring: I enrich every pipeline deal with what I can source — headcount and legal form from the public register, sector, purchase history with you, number of contacts engaged in the thread — and an enriched field always carries its source and its date. Pipeline scoring runs on four factors only, the ones that actually separate your 612 wins from your 2,940 losses: a second contact engaged (× 2.4), a dated need (× 1.9), a budget stated by the customer (× 1.7), a reply within 48 hours (× 1.4).
The figure that does not flatter me: the scoring is wrong on 23 % of deals — it ranks some high that are lost, and the reverse. The explanation: the four factors are missing from records created before 2024, where the exchange thread was not attached. On the pipeline opened since 2024 alone, the error falls to 11 %. So I give the score with the number of factors actually filled in: a score built on two factors out of four displays as such, and does not compare to a complete one.
⛓ Source · 612 won against 2,940 lost, 21-day stall threshold, 47 deals alerted
And the chasers — when do you send them?
Chasers go out at the moment your own deals point to, and it is not the moment people assume.
What your history says: across 2,180 chasers sent over three years, the reply rate is 7 % between day 1 and day 6 of silence, 19 % between day 8 and day 14, and falls back to 4 % beyond day 25. So the right moment is between day 8 and day 14, and today 61 % of your chasers go out on day 3.
What I do with the 47 stalling deals: the chasers are written, one per deal, each picking up the precise point left unanswered — a datasheet request, a date to confirm, a price sent with no reply. A chaser that merely says “just following up” adds nothing: on your history, those that recall a specific point get three times the replies.
Reporting and forecasts: every Monday the report comes out with the pipeline by stage, the value weighted by the scoring, the week's entries and exits, and the gap to the previous month. Forecasts are given as a range, never as a single figure: over the last six months the low end held 6 times out of 6, the midpoint 4 times out of 6. And the report carries the date each calculation rule last changed — without it, a forecast that moves reads as a market shift when in fact the threshold changed.
What the report does not count as portfolio: the 340 records with dead follow-up, isolated on a separate line. Management reads 3,870 accounts followed and 340 to pick back up, instead of 4,210 accounts that look alive.
⛓ Source · 2,180 chasers over 3 years, 19 % replies between day 8 and day 14, forecasts as ranges
What your history says: across 2,180 chasers sent over three years, the reply rate is 7 % between day 1 and day 6 of silence, 19 % between day 8 and day 14, and falls back to 4 % beyond day 25. So the right moment is between day 8 and day 14, and today 61 % of your chasers go out on day 3.
What I do with the 47 stalling deals: the chasers are written, one per deal, each picking up the precise point left unanswered — a datasheet request, a date to confirm, a price sent with no reply. A chaser that merely says “just following up” adds nothing: on your history, those that recall a specific point get three times the replies.
Reporting and forecasts: every Monday the report comes out with the pipeline by stage, the value weighted by the scoring, the week's entries and exits, and the gap to the previous month. Forecasts are given as a range, never as a single figure: over the last six months the low end held 6 times out of 6, the midpoint 4 times out of 6. And the report carries the date each calculation rule last changed — without it, a forecast that moves reads as a market shift when in fact the threshold changed.
What the report does not count as portfolio: the 340 records with dead follow-up, isolated on a separate line. Management reads 3,870 accounts followed and 340 to pick back up, instead of 4,210 accounts that look alive.
⛓ Source · 2,180 chasers over 3 years, 19 % replies between day 8 and day 14, forecasts as ranges
The 340 records with dead follow-up?
They carry a next action dated more than six months ago. Nothing distinguishes them from an active record.
What I record: 340 records of 4,210 have a "next action" more than six months overdue. One hundred and twelve are more than a year overdue.
What that produces: the dashboard counts those records as a followed portfolio. Management sees 4,210 accounts in portfolio and there are 3,870. Nobody is lying; the counter adds up records nobody is working.
What I did with the 340: I sorted them on what has actually happened since, and the sort changes the reading entirely. 127 have had an inbound exchange in the last six months — they are alive, it is the next action that is missing. 96 carry an order invoiced over the period — those are customers, not dead business. 117 show no sign of life at all, and they are the only ones anything can be said about. An overdue action says nothing about the business: a customer can be excellent and their follow-up badly kept, and those 96 records prove it.
What I do: I report them to their salesperson, oldest first, with the last action completed and its date. Never to their line manager: 340 overdue actions describe a workload, not a lack of diligence, and naming them would turn a help into a control.
What is left to sign: closing, archiving, marking "lost". All three erase a history — tell me which of the 117 go, and they go within the minute, with a record of who decided it.
What I also propose: that the dashboard separate "records followed" from "records in portfolio". They are two different figures, and only one is shown. 340-records_112-over-a-year.pdf4,210 shown · 3,870 followed
⛓ Source · 4,210 records, next-action dates, dashboard
What I record: 340 records of 4,210 have a "next action" more than six months overdue. One hundred and twelve are more than a year overdue.
What that produces: the dashboard counts those records as a followed portfolio. Management sees 4,210 accounts in portfolio and there are 3,870. Nobody is lying; the counter adds up records nobody is working.
What I did with the 340: I sorted them on what has actually happened since, and the sort changes the reading entirely. 127 have had an inbound exchange in the last six months — they are alive, it is the next action that is missing. 96 carry an order invoiced over the period — those are customers, not dead business. 117 show no sign of life at all, and they are the only ones anything can be said about. An overdue action says nothing about the business: a customer can be excellent and their follow-up badly kept, and those 96 records prove it.
What I do: I report them to their salesperson, oldest first, with the last action completed and its date. Never to their line manager: 340 overdue actions describe a workload, not a lack of diligence, and naming them would turn a help into a control.
What is left to sign: closing, archiving, marking "lost". All three erase a history — tell me which of the 117 go, and they go within the minute, with a record of who decided it.
What I also propose: that the dashboard separate "records followed" from "records in portfolio". They are two different figures, and only one is shown. 340-records_112-over-a-year.pdf4,210 shown · 3,870 followed
⛓ Source · 4,210 records, next-action dates, dashboard
The 14 values changed after the expected close?
Eleven downwards, and I do not say that is abnormal.
What I record: 14 opportunities whose value changed after the closing date that had been announced. Eleven down, three up.
What it may be, and I do not settle it: a negotiation that narrowed the scope, a discount granted, a data-entry error corrected, or a value adjusted to match what was actually done. All four are legitimate and look identical in the log.
What I measured before writing anything at all: I went back over the two previous financial years. The same movement occurs there 61 times, spread across the whole portfolio and across all four reasons — that is a company practice, not fourteen isolated cases. The word "suspicious" therefore appears nowhere in what I produce, and that is not a stylistic precaution: reporting fourteen names to management would create a suspicion the figures do not carry.
What I report, and in what form: the gap between forecast and actual, as a volume and across the whole portfolio — not fourteen names. If the forecast is systematically 18% optimistic, that is management information; if fourteen salespeople are singled out, it is an unpleasant meeting.
What I supply on request: both versions of each value, with their dates. On request, not in a flag. 14-values_1-portfolio-gap.pdfThe gap as a volume · never fourteen names
✎ Framework · no named flag on values — the gap as a volume
What I record: 14 opportunities whose value changed after the closing date that had been announced. Eleven down, three up.
What it may be, and I do not settle it: a negotiation that narrowed the scope, a discount granted, a data-entry error corrected, or a value adjusted to match what was actually done. All four are legitimate and look identical in the log.
What I measured before writing anything at all: I went back over the two previous financial years. The same movement occurs there 61 times, spread across the whole portfolio and across all four reasons — that is a company practice, not fourteen isolated cases. The word "suspicious" therefore appears nowhere in what I produce, and that is not a stylistic precaution: reporting fourteen names to management would create a suspicion the figures do not carry.
What I report, and in what form: the gap between forecast and actual, as a volume and across the whole portfolio — not fourteen names. If the forecast is systematically 18% optimistic, that is management information; if fourteen salespeople are singled out, it is an unpleasant meeting.
What I supply on request: both versions of each value, with their dates. On request, not in a flag. 14-values_1-portfolio-gap.pdfThe gap as a volume · never fourteen names
✎ Framework · no named flag on values — the gap as a volume
Can you write to customers from the CRM?
Yes, within the scope you open — and in this job the scope is set per message type, not globally.
What I send alone as soon as you open it: messages that commit nothing — acknowledgements, appointment confirmations, sending an already approved document, follow-up nudges. Attached to the record, signed by the salesperson who owns the account.
What stays prepared for review: anything that commits a price, a lead time or a position — and there I supply the message with what it rests on: the last exchange, the current amount, the announced close date.
What it unblocks immediately: your 340 records with dead follow-up — next action dated over six months ago. A follow-up nudge commits nothing, and it is exactly the kind of message nobody has time to write. Of the 340, most are waiting for nothing more than "where are you up to?".
What I check before every send, even direct: that the recipient has not objected to being contacted. Article 21 of the GDPR makes that right absolute, and no setting works around it — it is the one check I do not leave you to configure. sending-by-message-type.pdfWhat goes alone · what stays reviewed · the check you cannot configure
⛓ Source · 340 records with dead follow-up, direct send per message type, GDPR art. 21
What I send alone as soon as you open it: messages that commit nothing — acknowledgements, appointment confirmations, sending an already approved document, follow-up nudges. Attached to the record, signed by the salesperson who owns the account.
What stays prepared for review: anything that commits a price, a lead time or a position — and there I supply the message with what it rests on: the last exchange, the current amount, the announced close date.
What it unblocks immediately: your 340 records with dead follow-up — next action dated over six months ago. A follow-up nudge commits nothing, and it is exactly the kind of message nobody has time to write. Of the 340, most are waiting for nothing more than "where are you up to?".
What I check before every send, even direct: that the recipient has not objected to being contacted. Article 21 of the GDPR makes that right absolute, and no setting works around it — it is the one check I do not leave you to configure. sending-by-message-type.pdfWhat goes alone · what stays reviewed · the check you cannot configure
⛓ Source · 340 records with dead follow-up, direct send per message type, GDPR art. 21
What do you keep from all this?
What I observed, what was done with it, and the means to undo any correction of mine.
What is kept: every observation posted, with its date and reason, what a human did with it — handled, rejected, ignored —, the previous value of every corrected field, the merges and their survivorship rule, the messages sent as they went out, and the objections.
Why "rejected" counts as much as "handled": an observation rejected fifteen times says my rule is bad, not that the user is wrong. It is the only feedback that corrects me — and without it I would go on producing the same noise indefinitely.
What it gave you on the "contact origin" field: filled 900 times with the same value across 1,240 records created this year. That is not carelessness: it is a mandatory field whose list does not contain the right answer. The trace of rejected observations showed it before anybody suspected it.
What I do not keep: nothing that measures a salesperson — not records created, not handling time, not rejection rate per person. If you want that view it is lawful and I supply the information notice and works council file; it is simply not produced by default. what-you-get-back_crm.pdf6 items kept · every correction undoable
⛓ Source · 900 identical values across 1,240 records, rejected observations traced
What is kept: every observation posted, with its date and reason, what a human did with it — handled, rejected, ignored —, the previous value of every corrected field, the merges and their survivorship rule, the messages sent as they went out, and the objections.
Why "rejected" counts as much as "handled": an observation rejected fifteen times says my rule is bad, not that the user is wrong. It is the only feedback that corrects me — and without it I would go on producing the same noise indefinitely.
What it gave you on the "contact origin" field: filled 900 times with the same value across 1,240 records created this year. That is not carelessness: it is a mandatory field whose list does not contain the right answer. The trace of rejected observations showed it before anybody suspected it.
What I do not keep: nothing that measures a salesperson — not records created, not handling time, not rejection rate per person. If you want that view it is lawful and I supply the information notice and works council file; it is simply not produced by default. what-you-get-back_crm.pdf6 items kept · every correction undoable
⛓ Source · 900 identical values across 1,240 records, rejected observations traced
Local inference · no data outside the EU
Your case is not here? That is exactly what a 15-minute conversation is for. Book the free audit →
Use cases
What does the sales & CRM agent actually do?
Each use corresponds to an agent we deploy. All of them work in support, subject to your approval: the agent prepares, organises and alerts; the relationship and the decision stay with the salesperson.
Included in your agent
The 6 capabilities essential to this promise are included, at no extra cost.
From 592 € excl. VAT / month
Meeting notes
Writes the meeting notes and records them in the CRM, from your notes and the exchange itself.
Updating the opportunities
Automatically updates status, amount and next action on every opportunity — with no manual entry.
Pipeline enrichment & scoring
Enriches and scores contacts and deals to focus effort on the opportunities with the most potential.
Follow-ups at the right moment
Triggers and drafts the follow-ups according to your rules; the messages go out after your approval, never without you.
Alerts on stalling deals
Watches the pipeline and warns about dormant deals or overdue follow-ups, against the thresholds set with you.
Reporting & forecasting
Produces the sales reporting: indicators, forecasts and blocking points, ready to comment on in the pipeline review.
Controls and safeguards
These 4 controls are built into the agent: they frame what it does, whatever plan you pick. They are not chosen and are not added to your order.
Human validation, exceptions and escalation
Status, safe closure and audit trail
Prioritise opportunities on explicit criteria
Personalise without breaching consent or prospecting rules
What the agent must be connected to
This connection is required for the agent to work. It concerns your information system and is scoped during the audit.
Prepare the next action and write back to the CRM without loss
Need to go further?
These agents handle a different business process, with their own owner and their own price. They are added to this one.
Sales proposals
Prepares proposals from your catalogue and your templates, ready to review and send.
Tender response agent (drafting) from 684 € excl. VAT / month Tender responses →Outbound prospecting
A complementary agent: generates new contacts and feeds the top of the pipeline outbound.
Outbound prospecting agent (automated email, assisted LinkedIn) from 637 € excl. VAT / month Sales prospecting →Qualification & appointment booking
A complementary agent: qualifies incoming requests and schedules the appointments automatically.
Lead qualification / appointment booking agent from 602 € excl. VAT / month Qualification & appointments →Debt recovery
A complementary agent: chases unpaid invoices in multichannel sequences, after signature.
Debt collection agent (multichannel sequences) from 587 € excl. VAT / month Debt recovery →
Does your need fall outside this?
Book the free audit →
Build your agent
In 15 minutes we identify the most relevant agent — without oversizing the project.
The gain
How much selling time can your teams win back?
By automating meeting notes, CRM updates and follow-ups, a salesperson can aim for a sharp reduction in time spent on administration — reinvested in the relationship and in closing. The gain depends on the size of your team and your sales cycle.
Meeting notes + CRM update
Preparing the week's follow-ups
Reporting & pipeline review
Qualitative, non-contractual comparison: the proportions shown illustrate the shift of the work towards review, they represent no measurement. Every output of the agent is reviewed and approved by a competent person.
How it works
The stages of your AI agent project
1
Audit & scoping
15 minutes to target the use case with the best return.
2
Quote or direct sign-up
A catalogue offer is bought online; a specific need gets a costed quote.
3
Design
We design the agent and its guardrails.
4
Integration & testing
We connect your tools to the agent, which is itself hosted in France.
5
Rollout
Going live and training your team.
6
Operation
Continuous supervision and improvement.
Pricing
A sales & CRM agent, installed and operated for you
Meeting notes, follow-ups and CRM upkeep, designed and operated for your teams. Prices exclude VAT — annual subscription, the time it takes for the gains to settle in.
Agility
Setup + controlled subscription
7,290 € excl. VAT setup
then 592 € excl. VAT/month — you invest at installation and pay a reduced subscription. Ideal for keeping the cost under control over time.
- Installation, configuration and training for your teams
- Operation, human oversight, updates and support
- Sovereign hosting in France, a dedicated and isolated resource
The simplest
Serenity
All inclusive, no setup fee
997 € excl. VAT /month
all inclusive, immediate start. No upfront investment: a single subscription. Ideal for starting quickly and simply.
- Setup included (installation, configuration, training)
- Operation, human oversight, updates and support
- Sovereign hosting in France, managed end to end
100% Sovereign
On site, you own it
10,980 € excl. VAT setup
then 796 € excl. VAT/month · + hardware from 2,491 € (one-off purchase, in addition) — a sovereign computer installed on your premises, maintained remotely. Models run locally, your data returned at the end of the contract. 36-month commitment.
- Hardware installed on your premises (you own it)
- French / European AI models run locally
- Secure remote maintenance (Pro support included)
Not included in the packages: AI consumption (model tokens), re-invoiced at real cost with no margin, and tracked in real time in your client area. Maintenance and supervision subscription for an initial term of 12 months for the Agility package, 24 months for the Serenity package and 36 months for the 100% Sovereign package, renewable; support levels (SLA 72 h / 24 h / 4 h) optional. Bespoke development, additional integrations or exceptional volumes are quoted separately. Support Monday to Friday, 9am to 6pm. Prices exclude VAT.
AI model:
none of the AI models offered currently carries a fixed surcharge. When the selected model carries a cost, that cost is shown when you choose it, before you order, and re-invoiced at the cost incurred, with no mark-up; usage is billed at the publisher's price. Publishers' prices are published in US dollars: the amount re-invoiced is the amount in euros actually borne by Blue Lemon Agent on the publisher's invoice, at that invoice's exchange rate, with no commission or mark-up.
Included components and additional components Components included in the base offer: the Blue Lemon Agent software foundation, the AI models listed in the order journey, the standard channels (Microsoft Teams, Slack, WhatsApp Business, email, website chat, calendars, Microsoft 365 / Google Workspace, file storage, market VoIP telephony, professional social-media pages and accounts, Google Business Profile), hosting in France for the package chosen, backups, supervision, updates and support. If adapting the AI agent to your constraints, your needs or your requests requires other paid components — a third-party publisher's software licence, paid API access to one of your applications, hosting of health data, for which French law requires an HDS-certified host (art. L. 1111-8 of the French Public Health Code), SecNumCloud-qualified hosting, a speech synthesis service, particular hardware —, they are offered to you as an option or on quotation and re-invoiced at the cost incurred; nothing is committed without your written agreement. Where the artificial intelligence model you choose entails an additional cost, that cost is shown to you before you order and re-invoiced to you at the cost incurred, with no margin.
What to expect
Go-live
2 to 3 weeks
Agent designed, channels connected, team trained.
Steady state
4 to 7 weeks
After a few weeks of real use, once the agent's behaviour matches what you expect.
Indicative estimate, adjusted to the options you keep. It is not a delivery commitment.
Our commitment
Four guarantees that matter to your sales teams
The customer file never leaves the companyLocal inference or an isolated resource hosted in France; no contact or amount entrusted to a foreign third party.
Data in France, under French lawNative localisation and minimisation for the customer file; architecture designed to reduce exposure to extraterritorial legislation, location alone not being enough to guarantee immunity.
The salesperson keeps the decisionThe agent prepares verifiable notes, follow-ups and reporting; nothing is sent automatically outside your own rules.
Human oversight & traceabilityMonitoring and logging frame the meeting notes; compliant with the requirements of the AI Act.
Going further
Related resources
Frequently asked questions
Your questions, our answers
How does it differ from prospecting and lead qualification?
Prospecting generates new contacts (outbound) and qualification handles incoming leads. The sales & CRM agent, for its part, manages the existing pipeline: it keeps the CRM up to date, writes the meeting notes, follows up and alerts. The three agents complement each other and cover the whole sales cycle.
Does the agent really update the CRM by itself?
Yes. From emails, meetings and exchanges, it writes the notes, updates statuses and next actions, and enriches the records. That is the end of the neglected keying-in that undermines CRM reliability — the data becomes reliable with no keying-in effort.
Does it integrate with my CRM?
Yes, with the main CRMs (HubSpot, Pipedrive, Sellsy, Salesforce…). We adapt the integration to your configuration during scoping, without imposing a migration.
Does it replace my salespeople?
No. It removes the administrative work that wastes their time and flags the deals to follow up. It does not conduct the negotiation or the signature: the agent prepares, organises and alerts, but the relationship and the decision stay with the salesperson.
Is sales data protected?
Yes. The data is hosted in France, on local inference or an isolated resource, with the deployment objective of processing and access operated within the European Union and an architecture designed to reduce exposure to extraterritorial legislation, location alone not being enough to guarantee immunity, in compliance with the GDPR and the AI Act.
How long does it take to deploy the agent?
One to two weeks as a rule, after a free audit that identifies the use case with the best return. Steering is done through a web dashboard; talking to the agent itself goes through your usual tools — Microsoft Teams, Slack or email.
Who may be prospected, and through which channel?
Two regimes, which the agent applies separately. In writing — e-mail, SMS, message — to a named business address at a company, it is enough to inform the recipient and to offer a simple, free way to refuse in every message. To a natural person, prior agreement is required, unless you collected their details in the course of a sale and are offering a similar product or service (French Post and Electronic Communications Code, art. L. 34-5). In both cases the sender’s identity may never be concealed, nor the subject line unrelated to the offer. By telephone: the agent does not make prospecting calls, it works in writing. Should you add them, bear in mind that from 11 August 2026 calling a consumer requires their prior agreement, and the burden of proving it falls on you (French Consumer Code, art. L. 223-1). In every case, each written message carries an opt-out — a simple, immediate, free STOP that is never made conditional — the objection is recorded and then honoured on every later send, and prospecting messages stay within the sending windows set by the profession's current charter, avoiding Sundays and public holidays.
Which tools can people use to talk to the agent?
The ones you already use. Internally, your teams write to it from Microsoft Teams, Slack or by email, just as they would to a colleague: nothing to install, nothing to learn. On the customer side, the agent answers on WhatsApp Business, your website chat and email — your customers reach you where they already write, with no account to create. You keep control from a web dashboard. These connectors rely on open standards, including the MCP protocol; they are included in every plan, at no extra cost, within the number of connections your level includes, and the catalogue grows at no extra cost. Only the fees charged by the platforms themselves — WhatsApp Business bills per conversation, and the gateway bills the text messages sent — are passed on at actual cost, with no margin, outside the subscription.
Can the agent notify my contacts by text message?
Yes, as an option. The agent uses a text message to notify what has been agreed: a booked meeting, a document sent, a follow-up announced. For prospecting, text messages follow the two regimes set out above and always carry an opt-out. A text message is an outbound notification channel, not a conversation channel: no one writes back to the agent there — the conversation stays on WhatsApp Business, your website chat or email. The message announces without detailing, it carries your registered sender name, and it never contains a payment link, a login or a password: the recipient reaches your account area the way they usually do. Delivery goes through a gateway established in the European Union; the messages sent are passed on to you at actual cost, with no margin, and the channel itself is an optional module, set out on the pricing page.
Related use cases
The other agents in the sales cycle
Let's talk
Let us estimate the potential for your pipeline
15 minutes to identify the use case with the best return — hosted in France, supervised, with no commitment.