Custom knowledge systems

RAG systems
built around
your knowledge.

Bring the knowledge across your business into reach. Give your team an AI assistant that finds relevant information and shows where its answers come from.

From source documents to a working system, with retrieval, evaluation, and deployment shaped around your workflow.

Custom build · Scope and pricing agreed after discovery

Illustrative knowledge assistant
A question from your team

What does a new customer need before onboarding?

An answer, with its sources

Assign an account owner, confirm the implementation goals, and collect the technical requirements.

Customer onboarding guide § 2 · Getting started
Retrieve relevant passagesGround the answer

Example content, not a live product demonstration.

From documents to a working system

The answer is only part of the product.

A useful knowledge assistant needs a dependable path from source material to an answer people can check. We scope that entire path together.

  1. 01 / CONNECT

    Prepare the knowledge

    Choose the documents and repositories that matter. Plan ingestion, content structure, metadata, and updates.

  2. 02 / RETRIEVE

    Find the right context

    Design search and ranking around real questions. Preserve source links and apply the access rules your workflow requires.

  3. 03 / ANSWER

    Make answers inspectable

    Build an interface or API with source citations and a clear response when the available evidence is insufficient.

  4. 04 / MEASURE

    Know how it performs

    Evaluate retrieval, answer quality, latency, and cost. Hand over the checks and documentation needed to operate the system.

Built around a real workflow

Start with the questions your team keeps asking.

Focus the first version on a useful, measurable problem. Expand after you understand where it helps and where it falls short.

Internal knowledge

Help employees find policies, processes, and institutional knowledge across approved documents.

Customer support

Give support teams a way to draft answers from product documentation and review the sources before responding.

Research and operations

Search technical material, compare passages, and bring relevant evidence into recurring decisions.

A scoped engagement

A system your team can take forward.

We agree on integrations, hosting, ownership, and support before implementation. Model and infrastructure costs are part of that conversation.

Plan your build

A proposed build can include

  • Document ingestion and an update workflow
  • Retrieval pipeline and an answer interface or API
  • Source citations and insufficient-evidence handling
  • Access controls appropriate to the chosen sources
  • An evaluation set, results, and operating documentation
  • Deployment, team handoff, and optional ongoing support

Before we build

A few practical questions.

Already have a system or want an independent technical review? Explore RAG consulting →

Is this an off-the-shelf subscription?

This offering is a custom system engagement. We define the sources, features, deployment, pricing, and support around your needs before work begins.

Can we use our existing stack?

We’ll assess your current infrastructure, model providers, search tools, and security requirements, then choose integrations that fit the use case.

Will every answer be correct?

No system can promise that. Retrieval, citations, evaluation, and fallback behavior help make errors easier to detect and manage. High-impact answers should have an appropriate review process.

What does it cost?

Pricing depends on the sources, integrations, interface, evaluation, and deployment requirements. Start with an inquiry and we’ll work toward a defined scope and quote.

Experience behind the work

Engineering, informed by evidence.

Led by Christopher Peters, former Principal Data Scientist at Zapier and Chief Scientist at Touch AI, the practice brings together applied statistics, engineering, and product experience to build and evaluate useful knowledge systems.

About the practice

RAG systems / Start a conversation

What should your knowledge make possible?

Share a little about your users, your source material, and the answers they need. We’ll shape the scope around your business.

First
A conversation about your use case and constraints.
Then
A proposed scope, deliverables, and quote.

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