AI Agents & Copilots built on
your knowledge and tools
Build RAG copilots and agentic systems that retrieve correct information, draft outputs, and take actions—backed by evaluation and guardrails.
When copilots make sense
What you get
- Knowledge ingestion + chunking strategy
- RAG retrieval + citations behavior (where applicable)
- Tool integrations (APIs/actions)
- Eval framework (grounding/accuracy/refusal)
- Guardrails (permissions, policies, prompt controls)
- Deployment + monitoring + documentation
Copilot vs Agent
Built-in Guardrails
Permission-aware retrieval
Users only see what they're allowed to
Prompt controls
Prevent jailbreaks and misuse
Policy filters
Block prohibited content or actions
Action approvals
Human-in-the-loop for critical actions
How it works
Query
User asks
Retrieve
Search knowledge
Generate
Draft response
Validate
Check guardrails
Act/Respond
Output or action
Example workflows
Integrations & systems
ISO-backed delivery
Certified processes & security
Security-first
Enterprise-grade controls
Full documentation
Runbooks + handover
Frequently asked questions
How do you prevent hallucinations?
We use RAG with grounding, citation requirements, confidence scoring, and fallback to 'I don't know' for uncertain answers
Can it call our APIs safely?
Yes—with action approvals, rate limits, logging, and rollback capabilities for sensitive operations
Can we start with one department?
Absolutely. We recommend piloting with one team before expanding to validate the approach
Do you support role-based access?
Yes. We implement permission-aware retrieval so users only access content they're authorized to see
What data do you need?
Your knowledge sources (docs, wikis, tickets), access permissions structure, and integration endpoints
Ready to get started?
Let's discuss your use-case and map the fastest path to production.