The middle layer for enterprise AI.

KnowCore captures how your experts work and what they know, then hands it to your people and to the AI that does the work.

Start a pilotSee how it works

Works with Claude, Copilot, ChatGPT, Cursor and your own agents.

Recorded steps travel along a glass path, fork at an amber decision point, and both branches flow into a layered core of knowledge

01 · Process capture

Record the work once. Keep the process.

Your expert does the task the way they always do. KnowCore Conex writes down every step and the reasons behind it, so the process stops living in one person's head.

  • A screenshot for every step, in the order it happened
  • The reasons people say out loud, kept beside the step
  • Where people do it differently, the rule behind each way
  • No process maps to draw and no workshops to schedule
A recorded step, Click Escalate to manager, with three reasons people said out loud while recording it
One recorded step, with what three people said while doing it.

02 · Expert knowledge capture

Keep what your experts know, without asking them to write

AI does the asking and the filing. Everything lands in one Knowledge Core with its source, and what an expert confirmed outranks everything else.

Way inWhenWhat it keeps
AI interviewsWhile they talkAn AI interviewer asks the follow ups and draws out the judgment calls a recording cannot show.
KnowCore ConexWhile they workEvery click in order, a screenshot per step, and the reasons they say out loud.
DocumentsFrom what existsPDFs, decks and transcripts, ranked below what an expert confirmed.
Paste and SlackIn secondsA thread, an email chain, a note written after a call.

The gap loop · it keeps learning

Usage finds the gaps. Experts fill them.

Every question your people and agents ask shows what the core cannot answer yet. The expert who knows fills it in, and the next person gets the answer.

Questions are grouped and counted, never attributed. You see what the company does not know, not who asked.

Three knowledge gaps: questions nobody could answer, grouped by meaning, each with how often it was asked and a button to interview the owner

  1. An agent asks what nobody wrote down

    Every question from chat, the API or a connected agent is checked against what you know. A weak answer is recorded as a miss, not dressed up as a guess.

  2. Misses cluster into a gap

    Two people asking the same thing in different words is one gap. KnowCore names it and counts how often it comes up.

  3. The gap goes to the expert

    One click drafts an interview from the questions people actually asked and sends it to the subject matter expert who owns that core.

  4. The loop closes

    The answer lands in the core and the next agent that asks gets it, with its source. Nobody filed a ticket.

03 · Skills and workflows

Hand the work to anyone, or anything

Every captured process goes out in the form each worker needs. People get a guide, agents get a skill, and the repeatable work becomes a workflow that Conex test runs in your browser before anyone approves it.

  • A guide your team follows, screenshot by screenshot
  • A SKILL.md any agent can load, with the reasons behind each step
  • A workflow drawn from real recordings, edited on a canvas or by asking the builder
  • Nothing is approved until a test of that exact version passes
  1. StartA vendor invoice arrives
  2. In the browserMatch it to the purchase order
  3. Read a valueCompare invoice and receiving amounts
  4. DecisionDo the amounts differ by more than 2%?
  5. No
    DoneApprove for payment
    Yes
    A person does thisSend it back to the buyer

Test run passed in Chrome. Ready to approve.

A vendor invoice approval, captured in one recording, as the workflow it becomes.

04 · AI automation

Let Claude and Copilot do the task

Connect the AI tools your teams already use. They pull your skills, processes and expert answers from KnowCore and work through the task on their own, inside the access you set.

  • One MCP connection for Claude, Copilot, Cursor, ChatGPT and your own agents
  • Agents load the skill instead of guessing, and cite where each answer came from
  • Access is set per Knowledge Core, so an agent sees only what its credential allows
  • What an agent cannot answer becomes the next question for your expert

Connect once, at www.knowcore.ai/api/mcp.

claude · ~/ap-queue> Work through today's vendor invoices in the AP queue.

● knowcore.list_skills  "vendor invoice"
  └ Approve a vendor invoice, mined from recordings
● knowcore.get_skill  approve-a-vendor-invoice
  └ 6 steps, with the reasons behind them

● Invoice 4471  matches the PO, within 2%  ✓ approved
● Invoice 4472  differs by 6.4%  ↩ sent back to the buyer

● knowcore.ask_knowledge_core  "Who approves invoices from new vendors?"
  └ No confident answer. Logged as a gap for the AP core.

Done. 11 approved, 1 sent back, 1 question for your expert.
Illustrative: Claude Code working an AP queue with the skill KnowCore captured from one recording.

Questions before agents get access

Can we check every answer?
Each one traces back to the recording, interview or document it came from, and you can open the source.
What wins when sources disagree?
What an expert confirmed outranks what was captured automatically, and the tiers are visible.
Who sees what?
Access is set per Knowledge Core. Drafts stay private, and agents get exactly what their credential allows.
Does anything run without us?
No. A workflow runs only after a test of that exact version passes and someone approves it.
Are we tied to one model?
No. KnowCore is an open MCP server, so your knowledge outlives whichever model you use next.

Start with the person everyone interrupts

One process, end to end, in a pilot. It starts in an afternoon, not a procurement cycle.

  • Capture one process and interview the expert behind it
  • Ship it as a guide, a skill and a tested workflow
  • Point Claude or Copilot at it and watch it do the task

Start a pilot

By submitting, you agree to our Privacy Policy