Five disciplined practices that move your AI from experimental prompts to contained, measurable production vessels.
We deploy models inside versioned delivery containers with schema validation at the rim, canary pours, and rollback paths. Every release ships with accuracy baselines your ops team can defend in audit.
Greenfield or retrofit—we map your data estate into vessels with explicit capacity, retention rims, and permission boundaries aligned to PIPEDA expectations.
Multi-agent and human review chains run inside UI-bound vessels. No step executes outside its chamber; lineage is automatic.
Automated pours through validation, redaction, enrichment, and scoring gates. Metrics from precision panels feed your accuracy dashboard before anything reaches clients.
View pipeline visuals
We partner with SRE and platform teams to operationalize vessel health: runbooks, on-call playbooks, and crisp analytics surfaces that reflect containment—not vanity uptime.
Per-vessel accuracy, pour latency, and drift alerts in one porcelain-clean surface.
Sandbox vessels for stakeholder reviews without touching production rims.
Book a 45-minute architecture pour with our Montreal leads.
