We build Agents. You build the Future.
● Business offer — IT & new technologiesThe AI agent for tech teams: code, test and document faster, without exposing your code
Code generation, pull request reviews, bug and vulnerability detection, refactoring: a huge share of a development team's time goes into repetitive or low-value work. Your AI agent absorbs it. Testing and software quality, technical support and documentation are carried by dedicated agents, ordered separately. Three IT team journeys — the incident, the service request, the change — are architected but have not been through acceptance testing: this page does not sell them, it shows the already-open agents they draw on and names the steps no one carries yet. Data hosted in France; the AI model is called at its publisher, except with the Sovereign model option. With that option, your source code, your repositories and your intellectual property are never handed to a foreign service. The developer keeps the lead: the agent carries out what you have authorised, the decisions remain yours.
Updated on
Fictional simulation — not a client result
4 unit tests proposed, including the edge case — for review before the merge.
⛓ Sourced · your Git repository + PR #482 (read-only)
I am preparing a review summary for the PR, for your approval.
✎ Action · review comment ready — the developer approves the merge
For an organisation established outside the European Union, the law of its own country applies; at its request, we put equivalent safeguards in place (human review before any action, a log of the criteria, information for the people concerned).
In a tech team — IT services firm, web agency, software publisher, startup or IT department — a Blue Lemon Agent agent speeds up the repetitive tasks of the development cycle: code generation, review, testing, bug fixing, documentation and technical support. Data hosted in France; the AI model is called at its publisher, except with the Sovereign model option. With that option, your source code, your repositories and your intellectual property are never exposed to a foreign service, architecture designed to reduce exposure to extraterritorial legislation, location alone not being enough to guarantee immunity. The time saved is reinvested in design, architecture and product value. Live within a few weeks.
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.
Indicative estimate, to be confirmed by a pilot on your real files (general terms of sale, article 4).
Three options, one agent
A code generation and review agent (writing, review, tests, docs), installed and operated for you. Choose according to how you work. Prices exclude VAT — annual subscription, the time it takes for the gains to settle in.
Setup + controlled subscription
- Installation, configuration and training for your teams
- Operation, human oversight, updates and support
- Hosting in France, a dedicated and isolated resource
All inclusive, no setup fee
- Setup included (installation, configuration, training)
- Operation, human oversight, updates and support
- Hosting in France, managed end to end
On site, you own it
- Hardware installed on your premises (you own it)
- French / European AI models run locally
- Secure remote maintenance (Pro support included)
What does the agent for IT and new technologies actually do?
The journeys of an IT team — the incident, the service request, the change — are written into the registry and have not been through acceptance testing: the supervisor that would coordinate them is not for sale on this page. What can be ordered today: this page's code review base, at its price, and the agents below, each at its price on its own page.
Code generation & review
Writing code, reviewing pull requests, detecting bugs and vulnerabilities, refactoring — proposed, for approval before the merge.
Risks named and located on the change under review
A rounding that may drift, a query without an index, an edge case not covered: each point is named and tied to its line. The agent flags the tests that are missing and can propose some; test campaigns and software quality are the work of a dedicated agent, ordered separately.
Review report, ready to post on the pull request
A summary bringing together the points to settle, to be read before the merge; it is the developer who approves the merge.
This base does not coordinate the agents with one another: orchestrating the incident, the service request and the change is written into the registry, has not been through acceptance testing, and is not sold here.
Granting, changing and revoking access rights and equipment
The service request journey assumes that, once approved, someone actually grants, changes or withdraws an access right or a piece of equipment and then reports the evidence. No agent in the catalogue does this: that step stays manual, on your side.
Not yet in the catalogue — not orderable Be notified when it becomes available →IT asset inventory
Knowing, before deciding, which equipment is already assigned, which licence is still free, which access is already held — then recording the assignment once made. No agent in the catalogue keeps that record.
Not yet in the catalogue — not orderable Be notified when it becomes available →The agents that add on, each at its own price
Each handles another process, with its own owner and its own price; several are the ones the journeys above draw on. Their sum is not the price of a supervisor: chaining the steps, handing over between agents and testing those handovers are neither included nor sold.
AI web development agent
Pages, components and web integrations produced from your mockups: a sovereign AI agent, hosted in France, that speeds up your front-end teams.
Website development from 309 € excl. VAT / month Discover the agent →AI agent for mobile app development
A sovereign AI agent, hosted in France, that helps your teams build screens, business logic and APIs for your iOS and Android apps.
Mobile app development from 314 € excl. VAT / month Discover the agent →AI testing & software quality agent
Writing the tests, reproducing a bug, hunting a regression before going to production takes up a considerable share of the team's time — essential work that is rarely valued.
Testing & software quality (QA) from 272 € excl. VAT / month Discover the agent →AI agent for technical support & documentation
Technical support answers the same questions a hundred times, and the documentation always falls behind the code.
Technical support & documentation from 344 € excl. VAT / month Discover the agent →AI knowledge base agent
The information exists in your company — but it is scattered across procedures, contracts, an intranet and the memory of a few people.
Document agent (FAQ, knowledge base) from 353 € excl. VAT / month Discover the agent →AI IT helpdesk agent
The ticket, from triage to closure: routed to the right service, with the applicable procedure quoted and a wider incident spotted from neighbouring tickets. It holds the ticket; it does not diagnose and it executes nothing on your behalf.
Ticket management agent (IT helpdesk) from 302 € excl. VAT / month Discover the agent →AI cybersecurity & log analysis agent
Correlation of the events in the logs you open to it, triage of alerts, real signal told apart from false positives, and a documented investigation. The decision to stop and the remediation stay with your teams.
Cybersecurity agent (log analysis) from 311 € excl. VAT / month Discover the agent →AI project tracking agent
Deadlines, the chain of dependencies and slippage detection: enough to prepare a change and spot scheduling conflicts between two deployments. It does not approve the change and it does not deploy it.
Project tracking agent (tasks, deadlines) from 259 € excl. VAT / month Discover the agent →In 30 minutes we identify the most relevant agent — without oversizing the project.
See the agent at work
4 everyday 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.
Fictional simulation — not a client result
· An API key appeared in a commit on 01/08 on branch feat/export-csv. It is still valid and grants access to your transactional email service.
· A dependency with a published vulnerability has been in production for 23 days. The fixed version was released on 15/07.
· The TLS certificate for the partner API expires in 12 days. Renewal is manual on your side.
· Backup restores have not been tested for 8 months. The backups themselves run daily. morning-watch_4-flags.pdf4 flags · exposure and deadline
⛓ Source · repositories, dependency log, certificates, backup logs
Revoking a key cuts whatever it feeds. Here it serves transactional email: cutting it blind stops your order confirmations. The order matters more than the speed.
What I established, so you can decide in three minutes:
· The key appeared on 01/08 at 16:42, commit a3f91c.
· It is still present in history, even though a later commit removed it from the file.
· The repository is private — the exposure is internal, which is not nothing but changes the scale.
· It is used by two services, which I have listed with their environment variable.
The steps are attached, in order: create the new key, deploy it to both services, verify a send, and only then revoke the old one. All four are written, ordered and costed in minutes, and the repository purge command is ready; the step that can cut production carries your name, and that is what means someone warns first. exposed-key_steps.pdf4 ordered steps · 2 services concerned
⛓ Source · repository history, configuration of both services
Routing follows your organisation: the key to the technical lead and the commit author, both together and nobody else — an exposed secret circulated in a team channel is exposed a second time; the dependency to whoever maintains the service; the certificate to whoever is on call; the restores to the technical lead.
With a chase: 4 h on the key, 24 h on the certificate and the dependency, 7 days on the restores. Then a weekly summary: by subject, never by commit author.
And I do not stop at the flag: all four files are built. For the key: the purge command written for this repository, the list of clones to resynchronise, the revocation request drafted, and a branch replacing the secret with a reference to your vault, tested. For the dependency: the version bump on a branch, tests green. For the certificate: the renewal request pre-filled, with the exact names to cover. For the restores: the test script and the window where it disturbs nobody. Four subjects, four files ready, nothing to look up twice.
What is left to sign, and why that is an advantage: revoking a secret can stop production, merging commits everybody's branch, deploying puts it live, disabling a test removes a net. Those four gestures carry a name and a time — that is what means somebody always warns first. You approve, they follow on within the minute.
And I read what you have opened to me, repository by repository, every access logged and withdrawable on a word.
✎ Proposal · watch and chases to be configured — you set the thresholds
Fictional simulation — not a client result
5 of the 6 PRs are good to merge: approved, up to date with main, tests green, no migrations.
The sixth deserves thirty seconds: PR #519 carries a non-reversible database migration — a dropped column. It is correct, it is approved, and it does not replay backwards. Deploy all six together and your rollback plan no longer covers the whole release.
What I suggest, and it costs nothing: deploy the five, verify, then the sixth on its own. You keep a simple rollback on 95% of the batch.
The rest is ready: the release note written from the PRs, a summary of the new environment variables, and the post-deployment checklist. release-2.14_prepared.pdf6 PRs · 1 non-reversible migration
⛓ Source · 6 PRs, migrations, deployment history
What I do in that case, and it takes a minute: I isolate the test, trace the last commit that touched the code it covers, and say whether it fails reproducibly or intermittently. Across your last 30 failures, 11 were intermittent — and all eleven involved three tests, always the same ones.
That is the real subject: three flaky tests cast doubt on the whole suite, and push people to override by reflex. I have listed them, with their failure rate.
A proposal, if you approve it: on each failure, the report goes to the author of the last relevant commit, marked reproducible or intermittent, chased at 24 h. And a monthly flaky-test report to the technical lead — by test, never by author. A flaky test is a team debt, not the fault of whoever wrote it. flaky-tests_30-failures.pdf11 intermittent · 3 tests involved
✎ Proposal · failure diagnosis — no test is ever disabled
· Rounding that can diverge — Facture.php, line 214: the discount is applied after the line is rounded, whereas the rest of the code rounds after the discount. Replaying July's 4,800 invoice lines, 17 differ by one cent, and 2 by two cents on cascaded discounts. A cent on an invoice shows up in reconciliation, not in a test.
· Query with no index — FactureRepository.php, line 88: the filter is on client_id, date_emission and no index covers the pair. On the test dataset, 340 ms; at production volume the execution plan announces a full scan of 2.1 million rows. The index is written, the migration is ready, it is not applied.
· Edge case not covered — a credit note larger than the original invoice. The code lets it through and produces a negative net; no test exercises it.
· Edge case not covered — 0% VAT on an exempt line: the pro-rata division runs with no guard. The test exists but covers the standard rate.
· Untraced change — the wording of the invoice's statutory mention changes at line 302, and nothing in the PR says who asked for it.
The two missing tests are written and attached to the PR: credit note greater than invoice, exempt line. Both fail on the branch as it stands — which is what makes them useful. Making them pass calls for a business decision — refuse the credit note, or accept it and carry it forward — and that decision is not in the code.
What I do not carry here, and I would rather say so: the test campaign and software quality tracking belong to a dedicated agent, ordered separately. I flag and propose the tests missing on the change under review; I do not run your test plan.
⛓ Sourced · diff of PR #497, PostgreSQL execution plan, test coverage
Fictional simulation — not a client result
What the 14 tickets share: all concern an export above 50,000 rows, all on accounts with the "custom columns" option enabled, and all since version 2.13 of 22/07.
What the logs say: a server-side timeout at 30 seconds, reached from around 47,000 rows when the option is on. Below that, no occurrences.
What it is not: a general outage. 812 exports completed over the same period.
Two replies are ready: the one to the 14 customers — stating what happens, in which case, and offering the verified workaround (export in slices); and the technical ticket, with the trace, the observed threshold and the 2.13 commit that added the extra join.
Neither is sent. export-incident_14-tickets.pdf1 cause · observed threshold · verified workaround
⛓ Source · 14 tickets, server logs, 2.13 history
What I did: replayed three exports from the test dataset, at 40,000, 47,000 and 60,000 rows, option on. The first two pass, the third fails at the same second. Split into two slices of 30,000, it passes.
What I did not do: test on a customer's data. The test dataset was enough, and there was no reason to touch real data for this.
What the reply says, and does not: it gives the threshold and the workaround. It promises no fix date — that is a roadmap call, not a technical fact.
And an observation beyond these 14 tickets: 203 accounts have the option on and regularly exceed 50,000 rows. Eleven of them have exported since 2.13; the others have not yet. I can warn them before they open a ticket, with the same message — or wait for the fix. That is your call, and it is not obvious: warning 203 customers about a problem 192 have not met has a cost too. accounts-concerned_203.pdf203 accounts · 11 have already exported
✎ Support · workaround tested on the test dataset — sending stays with you
Fictional simulation — not a client result
The decision: architecture note ADR-014, of 12/09/2023. Reason: the service exposes amounts that must reflect the database to the second, because of a bank reconciliation screen used live by the accountants.
What contradicted it, and is written nowhere: the reconciliation screen was removed in April 2025, PR #331, replaced by an export. The reason behind ADR-014 has not existed for sixteen months.
What I measured before leaving it to you: over the last thirty days, the service takes 412,000 reads a day, 94% of them on data unchanged for more than an hour. A one-minute cache would cover those 94% and divide the read load by eight — the measurement is reproducible, and the query that produces it is in the note.
What the ADR's text does not say, and only you know: whether other implicit reasons weighed in 2023. That is why the question is put at the front of ADR-014bis, not in its conclusion — and why an architecture decision is signed: the signature is what lets it be read back in two years.
The draft of ADR-014bis is written, with both dated facts and the figure. ADR-014_and-what-made-it-stale.pdf1 decision · 1 fact that contradicts it
⛓ Source · ADR-014 of 12/09/2023, PR #331 of April 2025
Three of them govern choices still applied today — that is, rules the team follows for a reason that has gone.
What I have written for the seven: a dated banner at the head of each note — "premise stale since April 2025, see PR #331" — with the fact that justifies it and its reference. Seven banners, ready, and none applied: they are waiting on your agreement, because they alter a record.
Why a banner rather than a removal: a stale note stays visible and stays marked as such. Removing it would lose the history of the reasoning, which is often more useful than the conclusion — and that is precisely what the banner preserves.
What I can do next, on your approval: match each architecture note against the removals of components it mentions, and tell its author — or the technical lead if the author has left — that one of its premises no longer holds. A chase at fifteen days, a quarterly report.
Of the seven, two authors have left the team. That is precisely where written memory serves most, and where it is most fragile. architecture-notes_7-stale.pdf31 notes · 7 mention a removed component
✎ Proposal · notes matched — none is rewritten
Your case is not here? That is exactly what a 30-minute conversation is for. Discuss your project →
The stages of your AI agent project
Audit & scoping
30 minutes to target the use case with the best return.
Quote or direct sign-up
A catalogue offer is bought online; a specific need gets a costed quote.
Design
We design the agent and its guardrails.
Integration & testing
We connect your tools to the agent, which is itself hosted in France.
Rollout
Going live and training your team.
Operation
Continuous supervision and improvement.
Why tech is adopting AI — and why it distrusts consumer assistants
Development teams are the first to see the value of AI: code generation, review, testing, documentation. But they are also the first to measure the risk: entrusting your source code and your secrets to a foreign service is a leak of intellectual property.
! The issue
Tech teams face constant pressure on delivery deadlines, technical debt and quality, with developers who are expensive and in short supply. Yet plugging in a consumer code assistant often amounts to sending source code, secrets, database schemas and business logic to a service hosted outside Europe, subject to the Cloud Act — and sometimes reused to train models.
✓ Our answer
AI is only of lasting interest to a tech team if it is sovereign and confidential by design. Local inference or an isolated resource hosted in France, controlled read access to the repositories, systematic human oversight, merge and release decisions reserved to the developer: the speed gained is never paid for in lost intellectual property. The aim is not to replace your developers, but to give them back thinking time for architecture and product value.
Your code, your repositories, your IP: sovereignty & confidentiality
Source code and intellectual property are a tech company's most valuable asset. Here is how the architecture of our agents protects them, line by line.
Local inference
The agent can run on your infrastructure or on a team machine: no line of code leaves the network, nothing passes through a public cloud.
Hosting in France
Otherwise, with the Agility and Serenity packages, a dedicated, isolated resource hosted in France, under French law: data hosted in France; the AI model is called at its publisher, except with the Sovereign model option.
Reduced extraterritorial exposure
Architecture designed to reduce exposure to extraterritorial legislation, location alone not being enough to guarantee immunity for your code: our architecture stays out of the American hyperscalers' reach, even when hosted in Europe.
One isolated resource per client
No pooling: a strictly dedicated environment, and your code never trains a shared model.
Controlled access to the repositories
Role-based read access (RBAC), encryption in transit and at rest, secrets management and logging of actions.
AI Act: governed deployment
The agent carries out what you have authorised; no automated merge and no automated release; 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.
How much time can a technical team win back?
By equipping code review, test generation and documentation, a team can aim for a significant reduction in time spent on repetitive tasks — reinvested in architecture, design and product value.
Four guarantees that matter to a technical team
Your questions, our answers
Does my source code leave my infrastructure?
Is my code reused to train a model?
Is the confidentiality of my repositories and my IP guaranteed?
Can the agent really generate and review useful code?
Do we have to change tools or CI/CD pipeline?
Is this only for large teams or IT departments?
How long does it take to deploy an agent?
29 AI agents Blue Lemon Agent deploys for this scope
Other sectors equipping themselves with sovereign AI agents
Let us estimate the potential for your tech teams
30 minutes to identify the use case with the best return — hosted in France, supervised, with no commitment.