A data infrastructure and predictive BI that you run yourself, numbers carved to last.

At Karnak, the kingdom's accounts are still readable thirty centuries later. Your numbers deserve the same fate: real-time ingestion, data warehouse, modelling, dashboards and forecasts, the data layer your decisions and your agents rely on, open source, on your server or your cloud, with no licence that expires.

Data engineering: pipelines, change data capture, warehouse, data quality, the foundations before the building
Real-time dashboards and plain-language questions on your numbers, an archive that answers when asked
Forecasting, anomaly detection and causal inference on your history: reading the past to draw the road

00The forgotten century

There was a century when people built systems that last.

Builders left behind mechanisms, libraries and whole cities that ran without a subscription or a vendor. That knowledge did not vanish: it was buried under monthly invoices. We are on the road to find it again. Every section of this site is a stop on that road.

Take the road

Karnak1858Records carved in stone, still readable thirty centuries later.For you: data still readable in ten years, no licence to renew.

Machu Picchu1912A city fed with water by gravity alone, no pump, no bill.For you: agents running on your own server, no subscription.

Angkor1866A water network designed at the scale of a whole region.For you: a data layer that connects every tool you run.

Tananarivearound 1900The Queen's Palace, built on the heights by local craftsmen.For you: a team in Antananarivo that delivers, step by step.

The math The offers The catalog The method

Archive images, public domain and CC0: Francis Frith, Hiram Bingham, Émile Gsell, Rijksmuseum, via Wikimedia Commons.

01The math

You pay for AI twice. We stop the meter.

Once for the subscriptions and token bills that arrive every month. Once for the hours your teams still spend chasing quotes and rebuilding the same reports.

Vendor subscription

Closed models, billed per use

Billed every month, per seat or per token
Your data flows through the vendor
Price grows with usage
Cut off the day you stop paying

Wikolabs installation

Open or open-weight models, on your server

Paid once, at installation
Your data stays with you
Monthly cost close to zero, whatever the usage
Yours forever, even offline

Near zero

monthly cost, whatever the usage

32 GB

and a quantised model are enough to start

100 %

of your data stays with you

agents and systems in the catalog

Thirty minutes to find out what those subscriptions replaced at your company.

02Our offers

Six ways to work with us.

From a one-week audit to a sovereign agent installed on your premises, through data architecture, cloud, fine-tuning and IoT in the field. Pick the entry point that fits your situation, we adjust the rest together.

Audit and strategic advisory

A data-first information system before any agentic AI system, governed, costed.

We go through your processes, data and dependencies, pick the use cases, draw the target architecture and governance rules, and hand you a prioritized plan your leadership can decide on.

Timeline1 to 3 weeks

Map of processes, data and recurring costs
Quick wins ranked by impact and effort, budget per batch
Governance: access, confidentiality, GDPR, human oversight
Presentation to your leadership team

The tools we operate

03The catalog

Forty-eight agents and systems, sorted by function.

Each line is a production-tested system, built on specialized open-source models and pluggable into your stack. The detailed architecture lives on each offer's page.

Not sure where to start? Describe your need in one sentence and we point you to the matching catalog lines.

Sales Cycle / Outbound

See the category

One line speaks to you? Let's look at it together.

04The method

Six steps, from discovery call to production.

Daily check-in, weekly review, a demo at every sprint. You validate each deliverable before we move to the next.

01
Discovery call (30 min)
A call to understand your context, challenges, and goals. We identify together where AI can create the most value for you.
02
Scoping & proposal
We structure use cases, user stories, and business rules with you. You receive a clear proposal with scope, timeline, and delivery milestones.
03
Kick-off & access
Team introduction, collaboration tool setup, and access provisioning. The project starts in a structured and secure environment.
04
Sprints & bi-weekly demos
Daily standup, 1-2 week sprints, end-of-sprint demo. You validate every deliverable before moving to the next phase.
05
Testing, QA & production launch
Unit tests, UAT (User Acceptance Testing), bug fixes, and production deployment on your infrastructure or ours.
06
Support, optimization & roadmap
Post-delivery monitoring, performance tracking, new features, and scaling. Weekly review to steer the roadmap together.

1 of 6

05The team

Six roles, one team, the whole lifecycle.

From the agent engineer to the MLOps engineer: the profiles that carry your project from the first data pipeline to production monitoring.

Agentic AI engineer

Designs and deploys autonomous AI agents with memory, skills and tools: sales agents, support agents, market intelligence agents.

Data engineer and architect

Builds real-time data pipelines, warehouses (PostgreSQL, ClickHouse, BigQuery, Snowflake) and CDC architectures that power your agents and dashboards.

ML and LLM specialist

Fine-tunes, trains and deploys custom models (RAG, RLHF, multimodal embeddings, speech, vision) for your domain, your vocabulary and your accents.

Edge computing integration

Runs models next to the field: IP cameras, sensors, Raspberry Pi, NVIDIA Jetson, industrial boxes, with local inference, offline operation and deferred sync.

Automation specialist

Orchestrates your workflows with n8n, Zapier, Make and LangGraph pipelines to connect your tools and remove repetitive tasks.

MLOps and cloud engineer

Deploys, monitors and maintains your models in production on GCP, AWS or Azure, with CI/CD pipelines and full observability.

A dedicated team, a review every week.

06The founder

A path from code to data, then from data to the sovereign company.

Founder and Principal Architect at Wikolabs, a sovereign AI studio. He leads a bilingual team of agentic engineers, data architects, MLOps and full-stack AI specialists. MSc Big Data and AI, ESTIA France.

Guillaume Rakotonjanahary Tsantaniaina Amboarasoa

Founder and Principal Architect

MSc Big Data and AI, ESTIA France

Roadmap, from the first job to today

Stage completed
Full-stack developer and data engineer
Web and mobile applications, data pipelines, first warehouses.
Stage completed
Data scientist and machine learning engineer
Forecasting, classification and recommendation models shipped to production.
Stage completed
AI engineer and tech lead
Agents, RAG, vision and voice; technical leadership of bilingual teams.
Today
Founder of Wikolabs
Free companies from recurring subscriptions to external services: an autonomous, sovereign intelligence system, a smart and predictive data infrastructure, a monthly cost cut to the minimum.

07The hub

Madagascar, the hub for sovereign AI integration.

Thanks to local expertise trained on open models, data and on-site deployment, Antananarivo installs sovereign systems for Europe, the French Caribbean and Guiana, the Indian Ocean, Africa and India. UTC+3, delivery in French and English.

Engineers trained and based in Antananarivo
Installed on your premises, on your server or your cloud, wherever it is
Meetings in your time zone, documentation in your language

A meeting in your time zone, this week.

08The journal

What we write for executives.

Analyses on agentic AI, automation and data, without the jargon.

All articles

Apr 28, 2026Agentic AI and ROI: What the Numbers Reveal After 18 MonthsAgentic AI12 min read Apr 10, 2026Your Commercial Pipeline Is Losing 68% of Deals SilentlySales Automation10 min read Mar 18, 2026Natural Language BI: When Every Executive Becomes Their Own AnalystDecision Intelligence9 min read