RAG pipelines
Retrieval systems that find the right context from your documents and generate grounded, cited answers.
RAG & Agentic Systems
We build retrieval-augmented generation pipelines that answer from your documents and agentic systems that execute multi-step workflows autonomously - with guardrails, traceability, and human oversight.
Document pipeline
LiveIntake
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Classify
Document type
Extract
Fields & data
Validate
Rules & checks
Human review
What we build
Advanced AI architectures that go beyond simple chat to real work.
Retrieval systems that find the right context from your documents and generate grounded, cited answers.
Multi-step agents that plan, reason, use tools, and complete complex tasks autonomously.
Connect agents to APIs, databases, and business systems so they can take real action.
Hybrid search, re-ranking, and query expansion for high-precision document retrieval.
Guardrails, approval gates, and audit trails that keep agents accountable and predictable.
Coordinate multiple specialized agents to solve complex, cross-domain problems.
How it works
Every RAG response cites its sources so users can verify. Every agent action is logged and reviewable. When the system encounters uncertainty, it asks for human guidance instead of guessing.

How we work
A structured path to reliable, grounded AI.
We identify your data sources, document types, and the actions agents need to perform.
We architect the retrieval, generation, and agent orchestration layers.
We develop the system, optimize retrieval quality, and validate agent behavior.
We connect to your systems and deploy with monitoring and safety checks.
We refine retrieval accuracy and expand agent capabilities based on real usage.
The payoff
Knowledge access and task automation that scales.
Staff get accurate answers from your entire knowledge base in seconds, not hours.
Complex multi-step tasks run autonomously with human oversight where it matters.
Every answer is cited, every action is logged - verifiable and auditable.
RAG systems reflect the latest version of your documents without retraining.
Handle thousands of queries and tasks without adding headcount.
Grounded in your data, not the open internet - accurate for your specific context.
Under the hood
FAQ
Still deciding? These are the things teams ask us most - and if yours isn't here, a 30-minute call will cover it.
RAG (Retrieval-Augmented Generation) grounds AI answers in your actual documents instead of relying on training data. This means accurate, current, cited responses.
Chatbots answer questions. Agents take actions - they can search, calculate, call APIs, update records, and complete multi-step tasks with planning and reasoning.
We build with guardrails, approval gates, and rollback capabilities. High-stakes actions always require human approval.
RAG systems automatically reflect the latest version of your documents. When you update a policy, the system uses the new version immediately.
Yes. We integrate agents with APIs, databases, and tools so they can orchestrate work across your entire tech stack.
Tell us what you're trying to solve. We'll come back with a clear, fixed-scope plan - no jargon, no obligation.