01 — Discovery & threat modelling
We map data flows, integration points and failure scenarios before writing code. Privacy impact considerations for PIPEDA and BC PIPA are addressed early when personal information is in scope.
Control Surface
Cogni Circuit Labs builds AI assistants, agents and workflow automations that survive contact with real operations — not slide decks. From Vancouver, we ship production systems for Canadian teams who need reliability, auditability and a clear handoff when the pilot ends.
Why production matters
A demo that answers questions in a browser is not the same as an assistant that respects role-based access, logs every action and degrades gracefully when an upstream API times out. We design for the second problem from day one.
6–10 wk
Typical pilot window from discovery to staged rollout, depending on data readiness and integration surface area.
RBAC-first
Every assistant we ship is scoped to identity, tenant and data classification — not a shared chat window with god-mode permissions.
Runbooks
Handoff includes observability dashboards, escalation paths and operator documentation your team can maintain without us on retainer.
Engineering bench
We are not a novelty vendor shipping black-box widgets. Cogni Circuit engineers work in your environment — Azure, AWS or GCP, Postgres or Snowflake, ServiceNow or custom internal APIs — and we document every decision in plain language for stakeholders who do not live in Jupyter notebooks.
Our default architecture pattern pairs a governed retrieval layer with tool-calling agents that execute bounded actions: create a ticket, draft a summary, route a document, trigger an approval. Human review stays in the loop where your policy requires it, and we instrument latency, token spend and failure modes so you can see what the system is doing under load.
Whether you need a copilot embedded in a line-of-business app or an overnight batch agent that reconciles inbound PDFs against your ERP, we scope the smallest shippable slice first. That discipline keeps budgets predictable and gives your team a working reference implementation instead of a six-month science project.
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Delivery model
We map data flows, integration points and failure scenarios before writing code. Privacy impact considerations for PIPEDA and BC PIPA are addressed early when personal information is in scope.
Iterative sprints with weekly demos on real data (sanitized where required). MLOps hooks capture drift, hallucination patterns and operator feedback from the start.
Staged rollout with rollback plans, on-call runbooks and training for the teams who will operate the system after we leave the room.
Handoff that sticks
Consulting engagements fail when knowledge walks out the door. Every Cogni Circuit project ends with architecture diagrams, infrastructure-as-code where applicable, test harnesses for regression checks and a prioritized backlog for phase two. We train your developers and operators in working sessions — not a PDF attached to a final invoice.
Clients across British Columbia and the rest of Canada use us when internal AI experiments need an external engineering spine: someone who has shipped agents before, who knows how to negotiate with InfoSec and who will tell you honestly when a use case should remain a simple automation instead of a full RAG stack.
About the studioSignal detail
The Signal Graphite design language on this site mirrors how we think about systems: dark, readable surfaces; high-contrast status indicators; no decorative noise that hides a warning light. Your operators deserve the same clarity in the tools we build for them.
From intake triage bots for municipal service desks to document-heavy workflows in construction and professional services, we focus on measurable cycle-time reduction and error catch rates — metrics your leadership can audit without trusting a vendor dashboard alone.
Tell us about your workflow, your data estate and your timeline. We respond within two business days from our Vancouver studio.
Contact Cogni Circuit