● Business offer — Website development

The AI agent for web development: from mockup to code, without leaving France

Building a mockup into code, writing a component, wiring up an API, fixing a display bug: a considerable share of web teams' time goes into repetitive tasks rather than into architecture and product. Your AI agent absorbs that integration and plumbing work. Hosted in France — on local inference or an isolated resource — your source code never passes through a foreign service. The developer keeps the lead, and the code and the intellectual property stay with you.

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Hosted in France Source code protected GDPR & AI Act: governed deployment The developer decides

Updated on 07/09/2026

Deployed in a few weeks

Web development assistant · hosted in France

Build this Figma mockup of the “Pricing” page into our design system, as reusable, responsive components.

Mockup analysed. 3 components generated reusing your design system (colour tokens, spacing, typography): PricingCard, a monthly/annual PlanToggle and FeatureList. Responsive build (mobile, tablet, desktop) and accessibility attributes (ARIA roles, contrast) included.
The code follows your ESLint conventions — ready for review.
⛓ Sourced · your repository + design system, on an isolated resource

And the page's SEO? We have had indexing problems before.

Points checked: title tags and meta descriptions per page, Product/Offer structured data, server-rendered content for crawlers, and canonical tags to avoid duplicate content. 2 improvements proposed: preload the main font and fix a missing alt attribute.
I am preparing the pull request with those fixes, for your approval.
✎ Action · PR ready for review — the developer approves and merges

Local inference · no data outside the EU

Code 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 developer decidesThe agent proposes, the team reviews and merges

✦ In brief

For a web team, a Blue Lemon Agent agent turns your mockups into pages, components and integrations ready for review — HTML/CSS build, component generation, API wiring, accessibility and technical SEO — respecting your design system and your coding conventions. It runs on local inference or is hosted in France: your repository 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 on building is reinvested in architecture and product. Live within a few weeks.

100%

hosted in France in the target architecture

transfer outside the EU in the target architecture

uses ready to deploy on this scope

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

Why AI matters to web teams — and why they hesitate

Code assistance genuinely speeds up front-end building and development. But plugging a consumer tool into a repository means handing a foreign third party the company's source code, secrets and intellectual property.

! The issue

Web teams are caught between ever shorter delivery deadlines and accumulating build debt (mockups to code, components to factor out, display bugs, accessibility, technical SEO). Yet most consumer code assistants amount to sending your repository, your API keys and your intellectual property to a third-party service, often hosted outside Europe and subject to the Cloud Act, with the risk that your code feeds the training of third-party models.

✓ Our answer

AI is only of interest to a technical team if it is sovereign and confidential by design. Local inference or an isolated resource hosted in France, code and secrets that do not leave your environment, systematic human code review: the time saved on building is never paid for in lost intellectual property. The aim is not to replace the developer, but to give them back thinking time for architecture and product.

The decisive point

Confidentiality of the code: sovereignty & intellectual property

Your source code is one of your most sensitive assets. Here is how the architecture of our agents protects it, repository by repository.

Local inference

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

Hosting in France

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

Reduced extraterritorial exposure

Source code: architecture designed to reduce exposure to extraterritorial legislation, location alone not being enough to guarantee immunity.

Your code trains no model

Your sources and your secrets are never reused to train a third-party model: they remain strictly for your own use.

One isolated resource per client

No pooling: an environment strictly dedicated to your company and your repositories.

AI Act: governed deployment

An agent strictly in support; no code merged automatically; traceability and human review 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 events logged, their content, their retention period and who may access them are defined for the deployment chosen.

For the most sensitive environments, SecNumCloud and reinforced hosting 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.

Web development assistant · hosted in France

Four flags this morning, and two concern code I proposed myself.
· Three libraries added this quarter each introduce a call to a third-party server. Two came from my own proposals.
· A 340 KB dependency was added to format dates. The function used is eleven lines long.
· Your home page has gone from 180 KB to 1.2 MB in six months. No single change is responsible.
· Forty-one images with no alternative text in code I generated before a rule was set. morning-watch_4-flags.pdf2 third-party calls came from my proposals
⛓ Source · project dependencies, page-weight history, generated code

You introduced third-party calls yourself?

Two of the three, and I flag it because nobody else will see it.
What I record: three libraries added this quarter each load a resource from a server that is not yours — a font, an icon set, an audience measurement. Two were in code I had proposed.
Why it happens: it is how those libraries are documented. The official installation example points at a third-party server, and the code works immediately — the local alternative takes three more lines and nobody writes them.
What that produces, and it is not visible on screen: every visitor to your site sends their IP address and current page to three companies with no connection to your business.
What I now do, unasked: I write no code that calls an external domain. Where a library does so by default, I supply the local version and say what it costs — a few kilobytes to host, and an update to do yourself.
What I supply for the three existing ones: the domain called, what is sent, and the local replacement, ready. 3-libraries_2-from-my-proposals.pdfThe official example points at a third-party server
⛓ Source · 3 libraries, domains called, proposed code

How did you spot all that? And who do you tell?

I look at what you have opened to me: the project's code, its dependencies and their weight, the page-weight history, and what I produced myself.
Routing follows what can be fixed before going live: a third-party call flagged on the branch, before merging — afterwards it is in production; a disproportionate dependency to whoever wrote the change, with the measurement; a weight drift to the team, monthly, never to the author of one change; an accessibility defect in my own code to nobody — I fix it and I count it.
With a chase: before merging on a third-party call, monthly otherwise. Then a monthly summary: by type of gap and by page, never by developer.

What that gives you this quarter: three calls to third-party servers cut before merging and replaced by their local versions, 340 KB of dependency handed back to eleven lines of code, a home page brought down from 1.2 MB towards the 180 KB it started from, and 41 images that regain their alt text.
What you gain from tomorrow: your visitors stop sending their IP address to three companies that have nothing to do with you, the page renders on a mid-range phone, and the developer reviews a branch already measured: they merge in minutes instead of opening an investigation. The time taken back from integration goes to architecture and product.
On what I see: the repository is opened to me branch by branch, every read is logged, and access is withdrawn with a single word. And your source code leaves neither your environment nor France: no model training, no foreign service, exposure to the Cloud Act reduced by design.
The next step is ready: fifteen minutes to plug in your conventions and your design system, and I hand you the branch with the three local replacements.
✎ Framework · no call to an external domain, nothing put live

The weight going from 180 KB to 1.2 MB — whose fault is that?

Nobody's, and that is exactly the problem.
What I record: 61 changes touched the home page in six months. The heaviest added 94 KB. The median added 11.
Why nobody saw it: eleven kilobytes go unnoticed. No review blocks on eleven kilobytes, none is wrong not to block, and sixty-one times eleven kilobytes make a megabyte.
What I checked before naming anybody: the three heaviest changes total 180 KB out of 1,020. Dealing with them would leave 82% of the weight in place, and would point at three people for something involving forty. The subject is the median, not the tail — and that is what decides the remedy.
What I propose: a budget per page, decided by you, and a measurement at every change. Not a block: a figure shown next to the change — "this page will go from 940 KB to 951 KB."
What that gave over a trial month: of 14 changes, 4 were slimmed down by their author before merging. Nobody had asked them to — the figure was simply visible while it could still change. 61-changes_11-KB-median.pdfEleven kilobytes go unnoticed
⛓ Source · 61 changes, weight per change, trial month

And the 340 KB dependency for formatting dates?

Eleven lines used from a library containing thousands.
What I record: a 340 KB library was added. One of its functions is called, in three places, to display a date in French format.
What I do not say: that it should have been written by hand. A proven library handles cases you discover at the worst moment — time zones, clock changes, leap years. Eleven hand-written lines rarely handle them.
What I supply so it can be decided: the real weight after compression — 340 KB in source, 78 KB served —, exactly what the function used does, and two alternatives: a smaller library covering this case, and the browser's own function which also does it.
What I add, and it is always missing from this kind of decision: what the dependency costs when it is no longer maintained. This one's last release was 14 months ago.
And I do not merely recommend the replacement: it is written. It touches three files, it sits on a branch, and the date-rendering tests pass on the 41 pages that call the function — 78 KB less served, that is 8% of the home page's weight.
What remains is your review and the merge: replacing a library is tested and signed for, and the signature is not a formality — it is what gives a regression an owner. 340-KB_11-lines-used.pdfLast release 14 months ago
⛓ Source · 340 KB dependency, 78 KB served, 3 call sites

41 images with no alternative text in your own code?

Yes, and it is the most commonplace defect in any generated code.
What I record: before a rule was set, 41 images I produced had no alternative text, or carried an empty one.
Why: because alternative text cannot be inferred from an image. It describes what the image adds in its context — the same photograph is decorative on a home page and informative in a manual. I cannot know which, so I was writing emptiness.
What I do since: I produce the image with an alternative text to fill in, marked in plain sight, and I refuse to write emptiness. An empty attribute reads as a decision — "this image is decorative" — and it rarely is one.
What that gives: of 88 images produced since, 88 carry a text. 71 were written by a person, 17 explicitly marked "decorative". None is empty by default.
What I also check, unasked: colour contrasts, form field labels, and tab order. Three defects an agent introduces without knowing and that a browser never displays. 41-images_then-88-with-text.pdfAn empty attribute reads as a decision
⛓ Source · 41 earlier images, 88 images produced since

Can you put the fixes live yourself?

No, and it is not the same thing as merging code.
What I do: I propose the change, with what it alters visually — because an accessibility change sometimes moves something on screen, and nobody expects it.
What goes through you, and what that guarantees you: putting it live, triggering a deployment, and any modification on a live site — not even excepting an alternative text.
Why even an alternative text: because a live page is read by search engines and sometimes cached elsewhere. A change invisible to the eye is not invisible to everyone, and it is your publication schedule that decides the moment, not me.
The change itself is ready: written, dated, with its before-and-after capture. It is waiting on a review, not on a decision of mine — and it goes out the second the review is given.
What I do alone, continuously: measure — weight, contrasts, missing texts, outbound calls — on what is live as on what is not. Measuring changes nothing, and that is why I can do it without asking.
What that avoided: over twelve months, 4 of my proposals would have broken the layout on narrow screens. They were caught in review — because there was a review. 0-live_4-breaking-proposals.pdfA change invisible to the eye is not invisible to everyone
✎ Framework · nothing put live, nothing modified in production

On the quote form, can you write the code yourself?

The generation is done, so is the review of what I generated, and you get the two separately.
What the generation produced: the quote form in 320 lines, zero calls to an outside domain — the font and the icons are served from your own server —, and 14 KB once compressed, against the 340 KB of the date library of which only eleven lines were used.
What the review found in my own generation: 6 findings across 320 lines. Two matter: a date field with no associated label, and an error message signalled by colour alone — unreadable for eight per cent of men. The other four are repetitions I collapsed.
The figure that does not flatter me: across my last 18 generations, 5 carried a call to a third party introduced by an official installation example, and two got through review without my seeing them. What I did with it: the review now reads the dependencies before the code, and over the next 6 generations the count is zero. The next step I propose: put the 41 components already online through the same review — three hours of my time, and you will know which ones call a domain you do not host.
What stays with you: the merge and the release. I put up the branch, the review and the measurements; the name on the merge is a person's.
⛓ Source · 320 lines generated, 6 review findings, 5 third-party calls across 18 generations

Can you choose the technical framework for a new project?

I can give you a reasoned, ranked recommendation. The choice itself is signed for — because it commits hiring, not just code.
What I supply for each option: the skills it requires, what it costs to maintain, how many people at your end know it today, how often it breaks compatibility, and what leaving it would cost in three years.
What I add without being asked: a reasoned ranking, with the option I would pick and why. That is not an abstention — a comparison with no recommendation wastes everybody's time.
Why the signature matters here more than elsewhere: a technical framework determines who you will be able to hire for five years, and what that will cost. It is not a technical decision: it is a resources decision disguised as a technical one, and it carries the name of whoever settles it. My recommendation becomes yours the day you sign it, and it is ready today.
What I do without being asked: I flag what I introduced myself. Three libraries added this quarter each load a third-party call; two came from me. Nobody else would have seen it. comparison-and-recommendation.pdfThe 5 elements compared · the recommendation supplied · what stays a resources decision
⛓ Source · 3 libraries with third-party calls, 2 introduced by the agent itself

What do you keep from all this?

What measures the site — and nothing that measures those who build it.
What is kept: page weight over time, outgoing calls introduced and by what, dependencies and the share actually used, accessibility fixes and their date, and framework comparisons with their criteria.
The drift nobody saw: the home page went from 180 KB to 1.2 MB in six months, across 61 changes. The heaviest added 90. There is no culprit — and that is exactly the problem: no single change is big enough to be refused, and the sum is. Weight is now measured at every change, with the delta.
The textbook case: a 340 KB library added to format dates. Eleven lines used out of thousands.
What I publish against myself: before a rule was set, 41 images I had produced had no alternative text at all. It is the most ordinary defect of any generated code, and it is invisible unless somebody counts it.
What I still do not do alone: deploy. Merging code is reversible; a deployment is seen by visitors before anybody reviews it. what-you-keep_web.pdf5 items kept · weight measured at every change
⛓ Source · 180 KB to 1.2 MB across 61 changes, 340 KB for 11 lines, 41 images with no alt text

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 your web projects

Each use corresponds to an agent we deploy. All of them work in support, subject to approval by your team.

Included in your agent The 4 capabilities essential to this promise are included, at no extra cost.

From 594 € excl. VAT / month

Building mockups into code

Turning your Figma mockups into responsive pages and components, aligned with your design system.

Code generation & review

Writing components, functions and fixes, and reviewing pull requests before the merge.

Testing & quality (QA)

Generating the tests, checking accessibility and regressions, securing every release.

Technical knowledge base

Instantly find an architecture decision, a convention or a snippet in your repositories and docs.

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 Access the technical context with least-privilege permissions Run tests, security analysis and human review before any change Version, log, roll back and measure quality

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.

Mobile applications

Adapting your web interfaces into mobile applications and keeping the shared components in step.

Mobile app development from 609 € excl. VAT / month Mobile applications →

Technical support & documentation

Documenting components and APIs, and answering your team's technical questions.

Technical support & documentation from 664 € excl. VAT / month Support & documentation →

Does your need fall outside this?

In 15 minutes we identify the most relevant agent — without oversizing the project.

Book the free audit → Build your agent

The gain

How much time can a web team win back?

By automating the building of mockups, component generation and technical SEO, a team can aim for an appreciable reduction in time spent on repetitive tasks — reinvested in architecture and product.

Building a page from its mockup

Today · done by hand

Prepared by the agent, to approve

Creating a reusable component

Today · done by hand

Prepared by the agent, to approve

Fixing a simple display bug

Today · done by hand

Near-instant

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

Audit & scoping

15 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.

Pricing

Three options, one agent

A web development agent (building, components, technical SEO), 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.

Agility

Setup + controlled subscription

5,715 € ^{excl. VAT} setup

then 594 € ^{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

Order →

The simplest Serenity

All inclusive, no setup fee

909 € ^{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

Order →

100% Sovereign

On site, you own it

9,050 € ^{excl. VAT} setup

then 791 € ^{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)

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 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.

See the full price list →

Estimate my gains in 1 minute →

Our commitment

Four guarantees that matter to a web team

Source code never leaves your environmentLocal inference or an isolated resource hosted in France; no repository or secret entrusted to a foreign third party.

Code in France, under French lawExposure of source code to the Cloud Act and FISA 702 is reduced by design, that data being located and minimised in France; location alone does not guarantee immunity.

The developer keeps the decisionThe agent produces verifiable code and fixes; no merge is automated, and human review stays the rule.

Human oversight & traceabilityBuilding mockups into code: monitoring, updates and logging, compliant with the requirements of the AI Act.

Going further

Related resources

AI agents for business →Our full offer Sovereign AI hosted in France →Our confidentiality commitment Code generation & review →Writing and reviewing code, without exposing the repository

Frequently asked questions

Your questions, our answers

Can AI really build my mockups into code?

Yes, to a large extent. An AI agent reads your mockup (Figma, Sketch, or a screenshot), generates the pages and components respecting your design system and your conventions, and handles responsiveness and accessibility. The developer moves from manual building to review and approval, which is much faster.

Who owns the code the agent produces?

You do, entirely. The generated code, like your sources, stays your property. Our agents run locally or on an isolated resource hosted in France: your repository and your intellectual property are never reused to train a third-party model or shared with anyone.

Are my repository and my secrets confidential?

Yes. Source code is a sensitive asset: our agents run locally on a machine belonging to the team or are hosted in France, 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. API keys and secrets do not leave your environment.

Can the agent merge code automatically?

No. The agent proposes verifiable pull requests that your team reviews before merging. No code goes into production automatically: human review stays systematic, in line with the AI Act.

Does the agent respect our design system and our conventions?

Yes. We configure the agent on your design tokens, your existing components and your linting rules (ESLint, Prettier). The code produced follows your conventions, which reduces the gaps found in review and eases maintenance.

Does the agent also help with the site's technical SEO?

Yes. It checks title tags and meta descriptions per page, server-side rendering for crawlers, structured data, canonical tags and accessibility — all factors that determine indexing and rankings.

How long does it take to deploy an agent?

A few weeks as a rule, after a free 15-minute audit that identifies the use case with the best return, then a phase of design, integration with your tools (repository, CI, design system) and testing before going live and training your team.

Related use cases

Other uses for your technical teams

Code generation & review →Writing and reviewing code without exposing the repository Mobile applications →Adapting your web interfaces to mobile Testing & quality (QA) →Securing every release

Let's talk

Let us estimate the potential for your web teams

15 minutes to identify the use case with the best return — hosted in France, supervised, with no commitment.

Free audit (15 min) → Write to us