Half the agent demos on the internet fall apart the moment they touch real data. Ours don't. We build them the unglamorous way: one real job, your real tools, approvals and audit trails included. We've shipped them for startups and for corporations where compliance gets the final word.
Not chat toys — working software that completes jobs your team does by hand today.
Ask anything about your docs, wikis, contracts, and tickets — get accurate answers with citations, respecting user permissions.
Extract, classify, validate, and route invoices, contracts, claims, and forms — at any volume, with human review where it matters.
Lead enrichment, market monitoring, competitor tracking — agents that gather, verify, and summarize information on schedule.
Agents that act in your tools: update the CRM, draft replies, create tickets, reconcile records — with approval steps you define.
Specialized agents working together on complex pipelines — one researches, one drafts, one reviews — orchestrated and observable.
Daily report digests, inbox triage, data quality checks — agents that run on a schedule and escalate only when needed.
Every answer traces back to your actual documents — no hallucinated policies or invented numbers.
Update a document and the assistant knows immediately — no retraining, no stale answers.
Users only get answers from content they're allowed to see — your access controls carry over.
Scoped tools, approval steps for sensitive actions, and full logs of what the agent did and why.
Run in your cloud with your data residency requirements — nothing has to leave your perimeter.
The right components for each project, and no vendor lock-in. Ever.
You should be. Here's how we answer the hard questions.
An AI agent is software that doesn't just answer — it acts. Given a goal, it plans the steps, uses your tools and APIs (CRM, email, calendars, databases), checks its own results, and finishes the job: researching a lead, processing a document pile, or resolving a support ticket end-to-end.
Retrieval-augmented generation (RAG) connects an LLM to your own knowledge — documents, wikis, tickets, databases — so it answers from your real, current content instead of its training data. That means accurate, citable answers about your business, and updates take effect immediately without retraining.
We scope each agent to an explicit set of tools and permissions, add human approval steps for sensitive actions, log every decision for audit, and test against edge cases before launch. An agent can only do what we've wired it to do — nothing more.
Yes. We integrate with your existing systems via APIs and respect your access controls — the agent sees only what the requesting user is allowed to see. Deployments can run in your cloud, and data can stay entirely within your infrastructure.
We pick per project: the strongest current LLMs — Claude, GPT — vector databases like pgvector, Pinecone, or Qdrant, and agent tooling including MCP integrations, function calling, and evaluation frameworks. If requirements call for open-source or self-hosted models, we support that too.
Describe the job — we'll tell you honestly whether an agent can do it reliably, and prototype it on your real data.
