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● Public sector — Debt & local finance

AI agent for managing debt and local finance

An assistant that tracks the debt, prepares grant applications and supports budget execution — the officer and the elected member keep the decisions. Hosted in France, on a resource isolated for each authority: the financial data stays under French law. The AI agent assists, the authorising officer decides.

Hosted in France Financial data protected GDPR & AI Act: governed deployment Human decisions

Updated on

Deployed in a few weeks
Local finance assistant · hosted in France
Prepare the 2027 debt repayment schedule and the ratios for the budget orientation debate.
Table prepared. Outstanding debt at 1 January: €4.2m across 9 contracts, 2027 annual payment of €512k (including €98k of interest), average rate 2.1%, debt repayment capacity of 5.3 years. One variable-rate contract reaches the end of a phase in June — flagged for review.
Charts and briefing note ready for the debate.
⛓ Source · your loan contracts + M57 accounts
Put together the investment grant application for the energy refurbishment of the primary school.
Application assembled. Form pre-filled, balanced financing plan (grant sought at 40%, own funds, region), model resolution prepared, documents gathered: quotes, works schedule, certificate that work has not started. 2 documents missing flagged (site plan, energy statement).
Ready for approval before submission — the authorising officer decides.
✎ Action · application ready for review — the public officer 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 authorising officer decidesThe agent prepares, it never decides alone
✦ In brief

In the finance department, a Blue Lemon Agent agent tracks outstanding debt (repayment schedules, ratios, dashboards), pre-assesses and assembles grant applications (French state investment grants such as DETR and DSIL), and supports budget execution under the M57 public accounting standard — payment orders, revenue orders, flagging discrepancies. It runs on local inference or is hosted in France on a resource dedicated to and isolated for each authority: the financial data is never exposed to a foreign service, architecture designed to reduce exposure to extraterritorial legislation, location alone not being enough to guarantee immunity. The decisions remain those of the authorising officer and the deliberative assembly. Live within a few weeks.

2 days → 2 hr
assembling a grant application (illustrative)
100%
hosted in France in the target architecture
0
transfer outside the EU in the target architecture
7
uses ready to deploy for the finance department

Illustrative markers describing our offer — to be confirmed by a pilot in your authority.

The context

Why AI matters to local finance — and why it hesitates

Between the move to the M57 accounting standard, tracking the debt, the grant application rounds and day-to-day budget execution, the finance departments of local authorities combine technical complexity and volume. Every grant application not filed in time is funding lost for the area.

! The issue

The officer is caught between deadlines that cannot be negotiated — grant application filing, loan repayments, the budget timetable — and time-consuming preparation work: debt tables, financing plans, checks on accounting allocations. Yet most consumer AI tools amount to entrusting loan contracts, the authority's accounts and investment projects to a third party, often hosted outside Europe and subject to the Cloud Act.

Our answer

For public financial data, AI is only of interest if it is sovereign and confidential by design. Local inference or an isolated resource hosted in France, systematic human oversight, decisions reserved to the authorising officer and the deliberative assembly: the agent prepares decision-support material that can be checked, it takes no budget decision. The aim is not to replace the officer, but to give them back time for analysis and for advising elected members.

The decisive point

Protecting the financial data: sovereignty & compliance

Loan contracts, accounts, investment projects: an authority's finances are strategic data. Here is how the architecture of our agents protects them, authority by authority.

Local inference

The agent can run on a machine belonging to the authority: no data leaves the network, nothing passes through a cloud.

Hosting in France

Otherwise, a dedicated and isolated resource, hosted in France under French law — the financial data: processing and access within the European Union targeted by the architecture.

Reduced extraterritorial exposure

Against the Cloud Act and FISA 702, the architecture is designed to reduce the exposure of the financial data; location alone does not guarantee immunity.

One isolated resource per authority

No pooling of data: an environment strictly dedicated to your authority, guaranteeing the continuity of the public service.

Encryption & controlled access

Encryption in transit and at rest, role-based access (RBAC), strong authentication and logging.

AI Act: governed deployment

The agent is strictly in support; no commitment and no decision is automated; 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.

The public body in this demonstration

Fictional public body

Ville de Roche-sur-Ancelle — town of 9,400 inhabitants (fictional local authority)

Sector
Town of 9,400 inhabitants: main budget of €12.18m of actual operating revenue and €3.4m of investment, one ancillary budget for wastewater, M57 accounting framework applied since 1 January 2024
Headcount
112 staff, 4 of them in the finance department — a head of finance, two accounting officers and one debt and grants officer; the chief executive and the mayor, as authorising officer, close the chain
Public served
9,400 inhabitants, 41 grant-funded associations, 380 active suppliers; one council meeting a month, one budget orientation debate and three budget amendments a year
Order of magnitude
6,400 payment orders and 2,100 revenue orders issued a year, 9 loan contracts for €4.2m outstanding, 11 grant applications filed a year, 12 productions of debt tables and ratios
Tools in place
M57 finance software, debt management module, platform for sending payment orders to the public accountant, grant tracking spreadsheet, department mailbox — the agent plugs in read-only, nothing is replaced and nothing is migrated
Who decides
The mayor, as authorising officer, signs the payment and revenue orders and settles the orientations; the town council votes the budget, the tariffs and the borrowings; the head of finance settles every output before it is sent; the public accountant pays and collects — the separation of duties does not move
Points for improvement
214 payment orders out of 6,400 come back rejected by the public accountant — 3.3 %, and each rejection costs 35 minutes of rework and nine days' delay to the supplier; the debt table for the budget orientation debate takes 9 hours and is redone twelve times a year; a grant application takes 16 hours; and two eligible applications were not filed last year for want of time before the deadline — €186,000 of funding never asked for

At Roche-sur-Ancelle, four people hold the debt, the grant applications and the budget execution of a town of 9,400 inhabitants, against a calendar that does not negotiate: filing deadlines, loan instalments, budget orientation debate, budget vote. The exchanges below cover a full financial year, from the review of the nine loan contracts to the report presented to the town council. The agent runs on local inference on a machine inside the town hall: contracts, accounts and investment projects do not leave the network. The agent prepares; the authorising officer and the assembly decide.

This public body, its figures and the exchanges that follow were invented for the demonstration. They illustrate a common situation; they describe no real service.

Local finance assistant · hosted in France
I have reread your nine loan contracts and matched them against your M57 accounts: the 2027 instalment table and the ratios for the budget orientation debate are ready, and the matching has thrown up a discrepancy the calendar never leaves time to look for.
What your debt carries at 1 January 2027: €4.2m outstanding across 9 loans, 2027 debt service of €512,000, including €98,000 of interest and €414,000 of principal, weighted average rate of 2.1 %, debt repayment capacity of 5.3 years — €4.2m over €792,000 of gross savings for 2026. Your two other benchmarks: debt service weighs 4.2 % of your €12.18m of actual operating revenue, and the outstanding debt comes to €447 per inhabitant.
The discrepancy, and one single loan carries it. The €98,000 of 2027 interest is 2.33 % of the outstanding debt, while your weighted average rate is 2.1 %. The €9,800 difference comes from loan no. 4: principal outstanding of €800,000, revisable rate, a phase at 1.15 % ending on 30 June 2027, then reverting to the index provided for in the contract, estimated at 3.60 % for the second half. Over the four years still to run, the cumulative gap comes to €39,200, and the year-by-year detail is in the document.
What I propose, and there are six months left to decide: I put three costed options on the table — let it run, ask the lender to reset the rate before 30 June, or repay early out of the surplus. You choose on amounts, not on an impression. debt-schedule_9-loans-4-2-million-euros.pdfThe 9 loans line by line, the 4 ratios, loan no. 4 and its €39,200
⛓ Sourced · your 9 loan contracts, 2026 M57 accounts, debt schedule at 01/01/2027
Is 5.3 years good or bad? And on loan no. 4, I don't have the early repayment penalty to hand.
Two benchmarks answer that, and the first one is your own. Your debt repayment capacity was 6.1 years at 1 January 2025 and 5.7 years at 1 January 2026: you are at 5.3 years, improving for three financial years in a row, and the reason is readable — you have repaid €414,000 of principal a year without drawing any new loan since 2024. The second benchmark is the one your assembly set itself: the town council resolution of 16 December 2025 sets an alert threshold of 8 years. You have 2.7 years of headroom. As an indication, a town is commonly regarded as entering a watch zone beyond 10 to 12 years; that is a sector order of magnitude, not an enforceable rule, and I do not carry it in the note — the note quotes only your resolution, which is enforceable.
On the early repayment penalty, here is what I have and what I hand you to obtain it in two days. What I have: article 9 of your loan no. 4 provides for an actuarial penalty, with no capped figure in the contract — the amount depends on the reinvestment rate on the day of the request, and it is in no document you hold. What I have done: the request for an early repayment statement is drafted, quoting article 9, the contract number, the value date sought and the three alternative amounts to be costed — full repayment, partial repayment of €400,000, rate reset. You sign it, the lender answers within 48 hours, and I replay the three options with the real figure.
In the meantime, here is what the three options cost before the penalty, and the note is ready for the budget orientation report. budget-orientation-note_debt-structure-and-management.pdfNote and charts ready for the budget orientation report, three costed options
⛓ Sourced · loan contracts no. 1 to 9, 2024 and 2025 annual financial statements, resolution of 16 December 2025
When does the note come out? The budget orientation debate is set for the council meeting of 12 February.
It is written, and it is waiting on your reading — not on your drafting. The calendar holds comfortably: article L. 2312-1 of the French general local authorities code requires, in towns of 3,500 inhabitants and more, that the mayor present to the council a report on the budget orientations, the multi-year commitments envisaged and the structure and management of the debt, within two months preceding the examination of the budget. You vote the budget on 26 March; the debate on 12 February is inside the window.
What the note already contains: the structure of the debt loan by loan, the split between fixed and revisable rates — 7 fixed-rate loans for €3.4m, 2 revisable-rate loans for €800,000 and €0, the second settled in March —, the instalment schedule out to 2034, the four ratios with their three-year series, and the three options on loan no. 4, costed. Four charts are built: debt run-off profile, split of principal and interest within the debt service, series of ratios, and weight of debt service in actual operating revenue.
What I propose on top, and it takes ten minutes to decide: the report says nothing today about your multi-year commitments, although the text asks for them. I have taken your three programme authorisations in progress and their payment appropriations — €2.86m of authorisations, €1.12m of appropriations entered for 2027 — and turned them into a page that slots straight in. You keep it or you drop it; either way, the note is complete the day you read it.
✎ Framework · article L. 2312-1 of the French general local authorities code · budget calendar adopted on 16 December 2025
One last thing before I let you run on all this: our contracts and our accounts — where exactly do they go?
Nowhere, and that is checkable on your own machine rather than on my word. I run on local inference on a server in the town hall: the contents of a loan contract, of an annual financial statement or of an investment project cross no external network to be processed. Network egress: 0. Transfers outside the European Union: 0. Over a machine that talks to nobody, exposure to the Cloud Act and FISA 702 is reduced accordingly; location alone is not enough, and the exposure is documented for the configuration chosen.
What I read, and how you check it: the technical account through which I read has read-only access on the M57 finance software, the debt module and the supporting-document repository — insert, update and delete are refused, and the permissions display with one command. Entries produced by me in your software: 0. I prepare, you validate, your software records under your own identifier.
The five roles follow the job: accounting officers, debt and grants officer, head of finance, senior management, and the technical account. Out-of-role accesses recorded since go-live: 0. The log carries who asked for what, when, and what was produced.
And if you would rather administer nothing, the same thing runs on a dedicated, isolated resource hosted in France, under French law, shared with no other authority — the scope is exactly identical.
What I propose so that you do not have to take my word for it: a half-day dry-run exit. You switch me off, you check that the payment-order chain and the debt module work exactly as before, you switch me back on. The slot that costs you least is the Thursday afternoon of the second week of August — 11 payment orders on average in that slot, against 214 on a Monday in December. technical-framework_where-financial-data-lives.pdfLocal inference, read-only, 0 data outside the EU, 5 roles, dry-run exit
✎ Framework · local inference, technical account permissions, access log · articles 5 and 30 of Regulation (EU) 2016/679
The budget orientation debate is where we are put on the spot. What exactly do you prepare?
The preparation of the budget orientation debate and the financial notes that go with it — written and sourced, signed off by your head of finance before they reach the mayor.
What I prepare: the budget orientation report in your own template, the summary note for the councillors, and the meeting materials. The figures come from your own entries: €4.2 M outstanding across 9 loan contracts, the year's instalment contract by contract, 5.3 years of debt repayment capacity with the calculation set out above the result, the movement of real operating income over five years, and the status of the 11 grant applications filed.
What the financial notes carry in addition, and what was missing: for every table, the source of the line and the extraction date; for every variance above 5 % year on year, one sentence of explanation in plain French; and the contract whose rate changes in June, written into the note rather than discovered in the chamber — €39,200 of rate variance over the year.
What that gives back: preparing the debt table and its annexes takes 9 hours and is redone 12 times a year; reading over a prepared one takes 2 hours. More than 84 hours given back over the year on that item alone, rounded down.
What does not move: the orientations are settled by the mayor and debated by the council. The note sets out the figures, the options and what each one costs; it recommends none of them. A note that concludes in the assembly's place is no longer a financial note, it is a position — and it would be open to challenge as one.
The figure that does not flatter me: on my first preparation, 3 tables out of 14 carried an extraction date earlier than the latest budget amendment: the amounts were correct on the extraction day and wrong on the meeting day. Your head of finance caught it before it went out, not me. I now date every table to the day of the meeting and I block any output whose source is older than the last budget amendment voted: over the next 11 preparations, no date discrepancy.
⛓ Sourced · 9 hours down to 2 across 12 outputs, €39,200 rate variance written into the note
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

The uses of AI in the local finance department

Each use corresponds to an agent we deploy. All work in support, subject to the public officer's approval and the authorising officer's decisions.

Included in your agent The 6 capabilities essential to this promise are included, at no extra cost.
From 915 € incl. VAT / month

Debt tracking & dashboards

Track loan repayment schedules, prepare debt tables and ratios (debt repayment capacity, annual payments).

Grant applications (state investment grants)

Pre-assess and assemble the applications: forms, financing plans, documents and model resolutions.

Support for M57 budget execution

Prepare payment and revenue orders, check accounting allocations and make the entries reliable before approval.

Flagging discrepancies & anomalies

Detect execution gaps, duplicates and allocation anomalies before they become rejections.

Preparing the budget debate & financial notes

Write briefing notes, budget orientation reports and material for the deliberative assembly.

Check the documents in financing and grant files

Check quotes, invoices and certificates attached to grant applications and payment orders.

Controls and safeguards These 5 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 Sources, access rights and handling of questions with no answer Reconcile supporting documents, rules and accounting entries with an audit trail Handle discrepancies and validations before any accounting entry or payment
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.
Integrate with accounting and banking software and with approved platforms (French e-invoicing)
The gain

How much time can a finance department win back?

By automating debt tables, the assembly of grant applications and execution checks, the authority can aim for a clear reduction in preparation time — reinvested in analysis and in advising elected members.

Debt table and ratios for the budget debate
Today · done by hand
Checking and approval
Checking the allocations of a batch of payment orders
Today · done by hand
Prepared by the agent, to approve
Assembling a grant application
Today · done by hand
Review and approval
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

Three options, one agent

A local finance agent (debt, grant applications, support for budget execution), installed and operated for you. Choose according to how you are organised. Prices exclude VAT — available by direct award below the public procurement thresholds.

Agility

Setup + controlled subscription

10,580 € incl. VAT setup
then 915 € incl. 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
Order →
The simplest Serenity

All inclusive, no setup fee

1,505 € incl. 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
Order →
100% Sovereign

On site, you own it

14,966 € incl. VAT setup
then 1,160 € incl. VAT/month · + hardware from 2,989 € (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)
Order →
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 include VAT at 20%: as a public body that is not VAT-registered, you cannot reclaim it.
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 a local authority

Financial data never leaves the authorityLocal inference or an isolated resource hosted in France; no data entrusted to a foreign third party.
Data in France, under French lawFrench hosting and native minimisation protect the financial data, architecture designed to reduce exposure to extraterritorial legislation, location alone not being enough to guarantee immunity.
The authorising officer keeps the decisionsThe agent prepares tables, applications and entries that can be checked; no budget decision is automated.
Human oversight & traceabilityMonitoring and logging frame the debt tracking & dashboards; compliant with the requirements of the AI Act.
Frequently asked questions

Your questions, our answers

Does the agent take budget decisions?
No: it prepares and summarises; the decisions remain those of the officer and the elected member concerned.
Is it compatible with M57 and our financial tools?
Yes: secure integration with your financial management software, defined at the design stage.
Does the agent decide the budget choices?
No: it prepares the decision-support material; the decisions remain those of the authorising officer and the deliberative assembly.
Does it integrate with our financial software?
Yes: through secure integrations defined at the design stage (M57, debt management).
How long does it take to deploy an agent?
A few weeks as a rule, after a free audit that identifies the most useful use case, then a phase of design, integration and testing before going live and handing over to the department.
Where is the financial data hosted?
In France, on a resource dedicated to and isolated for each authority. GDPR: governed deployment. Depending on the need, the agent can also run on local inference, with no data leaving the network.
Do we need a technical team in-house?
No. The agent is designed, installed and operated by us: supervision, updates and maintenance are included. The department concentrates on analysis and advice.
Let's talk

Let us estimate the potential in your authority

A few minutes to identify the most useful use case — hosted in France, supervised, with no commitment.