Capabilities
The technical substrate behind operational AI.
Capabilities, not buzzwords. What we actually design, build and operate — on our own infrastructure as well as our clients'.
Agentic systems & orchestration
Multi-agent architectures that go beyond chat. Systems where agents plan, call tools, hand off to each other, and complete work end-to-end — with the determinism guarantees enterprises actually need.
Multi-agent pipelines
Planner / executor / verifier patterns; long-horizon task decomposition; persistent context and memory across runs.
Tool use & MCP integration
Model Context Protocol servers for first-class integration with enterprise systems — CRM, ERP, ticketing, internal data, document stores.
Workflow orchestration
Durable execution, retries, human-in-the-loop checkpoints, and clean separation of agent logic from orchestration plumbing.
Evaluation & reliability
Eval harnesses, regression suites and behaviour budgets — so agents don't silently drift after a model update.
Multi-provider LLM gateways
A single internal entry point for every LLM call across your organisation — with unified observability, capability-aware routing, quota arbitration and provider fallback. We design and operate gateways like this for our own ecosystem; we build them with clients who want the same posture.
Unified routing
One base URL, many providers (Claude, OpenAI, Mistral, Gemini, on-prem). Apps switch models or providers via configuration, not code.
Cost & quota arbitration
Per-app budgets, rate-limit pooling, automatic fallback when providers degrade or quotas exhaust.
Provider-neutral application code
Apps stay portable. Provider lock-in — and provider risk — sit at the gateway, not inside every codebase.
Activity log & audit trail
Every request captured with app, agent, model, latency and cost — the substrate for governance and chargeback.
Observability & evaluation
You cannot operate what you cannot see. We instrument AI systems for the same standard of observability as the rest of the production stack — traces, metrics, evals, and the dashboards that make them actionable.
Tracing & spans
End-to-end traces from user request through agent reasoning, tool calls and LLM invocations. Pydantic Logfire as our default substrate.
Quality & safety metrics
Hallucination rate, refusal rate, hand-off rate, escalation rate — tied to alerts and on-call rotations.
Continuous eval
Golden-set regression runs on every model bump. Production sampling for behaviour drift detection.
Cost & latency budgets
Per-feature and per-user budgets enforced at the gateway. Spend visibility for finance and engineering alike.
Governance & compliance
The frameworks that let AI systems operate inside regulated environments — and survive an audit. We work from existing risk and control libraries rather than inventing parallel ones.
AI governance frameworks
Policy, roles and decision rights for build vs. buy, model approval, change management and incident response.
Risk & control mapping
Mapping AI-specific risks (data leakage, prompt injection, hallucination, model drift) into existing enterprise risk taxonomies.
Auditability by design
Immutable activity logs, prompt and response retention policies, reproducible runs — the evidence chain auditors actually ask for.
Regulatory alignment
EU AI Act, GDPR, FINMA, sector-specific frameworks. Built into the architecture, not bolted on afterwards.
Sovereign & data-resident deployments
For environments where data cannot leave a given jurisdiction or perimeter. We design deployments that meet residency, confidentiality and sovereignty requirements without giving up modern AI capability.
Swiss & EU data residency
Provider selection, network egress controls and logging boundaries designed for FINMA, GDPR and Swiss confidentiality standards.
On-prem & private-cloud models
Open-weights deployments where appropriate. Hybrid architectures that route sensitive workloads on-prem and the rest to managed providers.
Confidential AI & PETs
Privacy-enhancing technologies where confidentiality is non-negotiable — including patterns from our deep-tech track record.
Sovereign provider integration
Mistral, Infomaniak and other European providers wired into the same gateway and governance layer as the global hyperscalers.
Want a deeper look?
Architecture review, gateway design, governance scoping, fractional CAIO — let's discuss what would help most.
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