We build AI agents thatactually run your operations.actually run your operations.
Graphor is an AI and agent engineering consultancy. We design, build and operate production-grade agent systems, from unstructured-data search to end-to-end workflow automation. Strategy to shipped, with one team.
Specialists in agents, whatever the domain.
Our products prove what we can build, but they are the output of a broader practice. We have shipped agents for sales ops, legal, support, finance and logistics. If a process runs on documents, conversations or judgment calls, we can automate it.
Agent systems
Multi-step agents that reason, retrieve and act inside your stack: support, sales ops, back office and beyond.
Agentic memory & RAG
High-performance retrieval systems tailored to your data, so agents answer from your knowledge with verifiable sources.
Workflow automation
Map a manual process end-to-end and replace the repetitive 80% with reliable, auditable automation.
Chatbots & copilots
Assistants grounded in your context for customers and internal teams, with clean handoff to humans.
Evaluation & MLOps
Telemetry, evals and monitoring that keep agents accurate in production and catch regressions before your users do.
AI advisory
Roadmaps, build-vs-buy calls and architecture reviews from a team that ships agents weekly, not slideware.
What happens inside one of our agents.
Every agent we ship follows the same discipline: each step is observable, each output carries its source, and a human can step in at any point.
inbox.receive()step 01 / 6Receive
A new input lands: an email thread, a support ticket, a batch of PDFs, a webhook from your systems. No forms, no manual triage.
Consulting, productized.
Patterns we kept rebuilding for clients became standalone platforms. Use them directly, or let us build on top of them for you.
Graphor DocumentAIplatform & API ↗
Turn documents into a private knowledge database your AI can trust. Graphor DocumentAI parses, chunks, indexes, grounds and answers over your unstructured data, with drop-in adapters for your stack. It is the retrieval engine behind our client agents, available as a platform and API.
Legal.Opsvertical solution ↗
Legal back-office automation for high-volume firms. Graphor connects incoming demands, documents, owners and next steps into cases the team can act on, with full traceability and human control. Born from client demand, now a dedicated offering.
Need an agent outside these? That's most of what we do.
Start small. Advance with proof.
We don't sell transformation programs. We pick one recurring queue, prove the agent on a small batch of real cases against a clear success criterion, and only then integrate with your systems.
01Discover
We map the process, the data and where judgment actually lives. One week, concrete scope.
02Design
Agent architecture, guardrails and success metrics, agreed before a line of code.
03Prove
A working agent validated on a small batch of your real cases, before any system integration.
04Operate
We monitor, evaluate and improve in production, or hand off cleanly to your team.
Controlled environment
First runs use synthetic data or a corpus your team pre-approves. Nothing touches production systems until it earns it.
Human review
Critical decision points stay under human validation until measured quality justifies automating them.
Staged homologation
Your IT validates data access, permissions and integrations phase by phase before go-live.
Agents already on the job.
BD & SDR orchestration agents
Lead classification and prioritization, conversation handoff and routing, CRM integration and AI-driven follow-ups feeding a mid-market sales team.
Support copilots on internal knowledge
Agents grounded in product docs and past tickets resolve routine cases and draft the rest for human review.
Conversation intelligence & analytics
Chat, email and Slack conversations turned into sentiment, trends and engagement insights in real time, integrated into existing workflows.
Back-office automation at case intake
Scattered email threads and attachments become consolidated cases with state, owner, deadline and verifiable sources: the work that became Legal.Ops.
The strategy exists. The hours go elsewhere.
Most operations don't fail for lack of a plan. They fail because the plan runs on people reading, copying and forwarding information that software should handle.
Data lives in email, drives, ERPs and chat. Consolidating it eats the week, and the insight arrives after the decision was needed.
Contracts, threads, transcripts and PDFs that no dashboard reads. The knowledge exists; retrieving it means asking whoever was there.
Every step needs a human to read, copy, check and forward. Headcount scales linearly with volume, and errors scale with fatigue.
Common questions.
No. Graphor DocumentAI is our own retrieval engine and it makes projects faster, but we build on whatever your stack requires: your cloud, your models, your vector store. The consultancy comes first; the products are tools.
We start in a controlled environment with synthetic data or a pre-approved corpus. Critical decision points stay under human review until quality justifies automation, and your IT validates data access, permissions and integrations before anything touches production.
The first working agent typically runs in your environment within weeks. We prove it on a small batch of real cases against an agreed success criterion before integrating with your systems.
A scoped discovery first, then a proof on real cases before you commit to a full build. You always know what the success criterion is and what it costs before the next phase starts.
Either. We can monitor, evaluate and improve agents in production as an ongoing service, or document and hand off cleanly to your engineering team.
It diagnoses where agents pay off, designs the architecture — models, retrieval, integrations, guardrails — and builds and operates the system until it runs reliably in production. In our case, with the same engineers who build Graphor DocumentAI.
With the success criterion defined up front: we prove the agent on a batch of real cases, measure it with evals, integrate with your systems under human review and only then automate — with telemetry and monitoring to keep quality up after go-live.
Have a process that shouldn't need humans?
Tell us about it in a 30-minute call. We'll tell you honestly whether an agent can do it, and show you how we would build it.