AI that compounds, governance that holds.
Strategy, build, data, run, evaluate, enable, govern. Wouessi runs the full AI surface, sequenced the way our buyers actually use it.
Wouessi runs the full AI surface, end to end. Strategy, build, data, run, evaluate, enable, govern, and industry frameworks. Not a single button, an entire supply chain. Below is what we ship, sequenced the way our buyers actually use it.
AI Strategy and Advisory
Use-case discovery
We map where AI changes the unit economics, where it removes a bottleneck, and where the right answer is just a workflow fix.
Buy, build, partner
We give you the trade-off honestly, even when 'do not build' is the answer.
ROI and risk modeling
Cost of inference, cost of evaluation, cost of governance, cost of getting it wrong. We do the math before you commit.
Governance design
Roles, gates, escalation, and the named owners your audit committee will ask about.
Build the system
Retrieval-augmented generation
Production RAG with chunking, evals, citations, and a replay envelope so an auditor can review what was retrieved long after launch.
Agents
LangGraph or custom finite-state agents with tool access, scoped permissions, and append-only decision logs.
Fine-tuning
When prompting or RAG is not enough, we fine-tune open-weight models on your data with safe fallback paths.
Multi-modal
Voice, vision, document parsing, OCR, and structured-output extractors trained against your real document archive.
Data foundations
Retrieval and lakehouse
Vector stores (Postgres + pgvector, OpenSearch, Pinecone), feature stores, and the data contract that keeps them consistent.
Lineage and provenance
We instrument data movement so you can answer 'where did this answer come from' for every model output.
Privacy boundary
Where customer data is, where it is not, and how the model can never see what it should not see.
Sovereign deployment
On your VPC, on-prem, or in your cloud account. We do not require data to leave your perimeter.
Run and observe
Inference infrastructure
Self-hosted Kubernetes, vLLM, Ollama, or managed APIs. Scaling that fits your traffic and your budget, not a vendor's quarterly target.
Observability
Latency, cost, accuracy, drift, and the user-experience signals that matter. Dashboards your engineers and your CFO can both read.
Cost control
Token budgets, cache strategies, request shaping, and the governance to keep a popular feature from blowing through quota.
Evaluate and govern
LLM evaluations
Curated test sets, regression harnesses, and golden examples that survive the next model upgrade.
Red team and adversarial testing
We try to break it before users do, and we keep the playbook so your team can keep doing it.
Hallucination detection
Confidence scoring, citation requirement, and graceful 'I do not know' behaviors.
Bias and fairness audits
With documentation a regulator can read.
Responsible AI policy
NIST AI RMF, ISO 42001, EU AI Act, Canadian AIDA, and the governance tooling to keep them honest.
Enable your team
Prompt libraries
Versioned, tested, and tied to evaluations so changes are visible, not invisible.
Enterprise training
Cohorts that turn skeptics into builders. Bilingual.
Copilot enablement
From IDE copilots to internal customer-service copilots with proper observability.
Industries we ship into
Banking
OSFI E-23 alignment, replayable model decisions, governance evidence.
Insurance
Claims triage, underwriting copilots, and the regulator-ready audit trail.
Healthcare
HIPAA in the US, PHIPA in Ontario, residency in your province by default.
Government
Protected B by default, AODA from day one, bilingual at the architecture layer.
Retail and logistics
Inventory and ops AI, with measurable cost-of-goods impact.
Bring us the AI question you have been chewing on.
Twenty-minute call. We tell you whether AI is the right answer, and if it is, the smallest useful next step.