AI Agent Integrations
Design and deploy AI agents that connect to your tools, follow your rules, and move work forward with measurable reliability.
RAG and agents, without the fairy dust
When the agent needs facts, we ground it in your docs and data with retrieval, citations, and guardrails. When it needs to act, we give it tools with permissions.
Common builds: customer support answer engines, internal SOP copilots, catalog enrichment agents, and analytics copilots.
What you get
- Agent workflows for triage, drafting, routing, and approvals
- RAG-backed answers grounded in your knowledge base
- Tool use via APIs, webhooks, and modern agent connectors
- Guardrails, evals, and human-in-the-loop checkpoints
- Observability: logs, cost tracking, and quality scoring
Deliverables
- System architecture + data flow diagram
- Agent prompt library + versioning strategy
- Deployed agent(s) with role-based access
- Evaluation harness (gold sets + regression tests)
- Runbook + handoff training
FAQ
Do you build on OpenAI, Anthropic, or open source?
Yes. We choose the model based on your needs: quality, latency, cost, and privacy.
Can agents take actions in our tools?
Yes, when appropriate. We prefer constrained actions with approvals for anything risky.
What’s the safest first use case?
Ticket triage, content briefs, internal search, and reporting assistants tend to ship fast and safely.
Want this in your stack?
We’ll start with your workflow, not a tool. Then we’ll design the smallest system that produces the outcome.