Sourcewell Request early access

Knowledge quality for enterprise AI

Keep your AI’s knowledge current.

AI assistants are only as reliable as the documents behind them. Sourcewell finds outdated policies, duplicates, and conflicting instructions in your source libraries — so your team can review and fix them before they reach the assistant.

Request early access Try the review panel →
  • Every flag is reviewed by a person
  • Exact matches and model inferences kept separate

Your assistant can’t tell which policy is the real one.

01

Outdated policies keep answering

Retired terms stay in the library long after the business changed them, and retrieval has no way to know.

02

Two documents, two answers

A finance policy and a support macro disagree. The assistant quotes whichever ranks higher that day.

03

Nobody owns the source

Copies multiply across folders with no owner, no review date, and no record of what was approved.

Product preview

The review panel

Pick a finding from the queue. Compare the highlighted passages, then record which source is current. All documents here are fictional.

sourcewell · Support Knowledge · Review queue

Demo only. In Sourcewell, decisions are stored with reviewer, timestamp, and the passages they relied on.

How findings are labeled

Certain matches and model judgments are never mixed.

Deterministic

Exact duplicates

Identical files are matched by content hash. There’s nothing to infer — the bytes match or they don’t.

Method
SHA-256 content hash
Shown as
Match / no match
Similarity score

Near-duplicates

Passages that say almost the same thing are found with embeddings and shown with their score, side by side.

Method
Embedding similarity search
Shown as
Score + aligned passages
Model-inferred

Potential contradictions

A language model suggests passages that may conflict and explains why, citing the exact text. It’s a lead, not a verdict.

Method
Grounded LLM analysis
Shown as
“Potential” + supporting passages

Every flag needs a person to sign off. Sourcewell never changes a document or an assistant’s knowledge on its own.

What’s in the first release

Everything you need to keep a source library honest.

Library uploads & scheduled scans

Upload document collections, including scans, then re-check them nightly, weekly, or on your own schedule.

Ownership & revision tracking

Every document has a named owner and a full revision trail, so you always know who to ask.

Duplicate & near-duplicate detection

Exact copies and closely similar passages, each labeled for what it is.

Potential contradiction flags

Possible conflicts shown with the supporting passages from both documents, side by side.

Review deadlines & stale indicators

Set review cycles per document and see what’s overdue before it becomes a wrong answer.

Assigned review tasks

Send each finding to the right owner with a due date, and track it to resolution.

Approved-change history

A permanent record of every decision: who approved it, when, and the passages they relied on. Ready for audits and handovers.

Workflow

From a messy library to approved sources, in six steps.

  1. 1

    Import documents

    Upload collections; every file is versioned.

  2. 2

    Extract content

    Text and structure, including scanned PDFs.

  3. 3

    Compare

    Versions and passages across the whole library.

  4. 4

    Flag issues

    Duplicates, stale sources, potential conflicts.

  5. 5

    Assign review

    Route each finding to its owner with a deadline.

  6. 6

    Approve changes

    Decisions are logged to the change history.

Built for

The people accountable for what the assistant says.

Knowledge managers

One queue for every stale, duplicated, or conflicting source, with owners and deadlines attached.

AI engineering teams

Cleaner retrieval sources and a reviewed record of which documents are approved to feed the assistant.

Support operations managers

Catch the macro that contradicts policy before an agent, or a bot, quotes it to a customer.

  • SaaS
  • Customer support outsourcing
  • Professional services

AWS Infrastructure

Built on AWS, serverless from day one.

Sourcewell uses an AWS-first architecture to securely manage document ingestion, embeddings, and finding orchestration. Data remains in managed AWS services.

Build plan

Start with the documents. Connect systems later.

First release

Uploaded collections

  • Uploaded document collections
  • Version comparisons
  • Review queues and assigned tasks
  • Approved-change history
Next

Source-system integrations

  • Connect the systems where documents already live
  • Sync ownership and revisions automatically
Future

Publish approved knowledge

  • Push approved changes to external AI systems
  • Not available today. Approved changes are exported and applied by your team.

Pricing

Subscriptions based on workspace and document volume.

Sourcewell is currently onboarding pilot customers. The plans below reflect the anticipated commercial structure once pilots validate our core workflows. Pricing is confirmed during early access.

Team

1 workspace
up to 5,000 documents

  • Uploads and weekly scans
  • Duplicate and stale detection
  • Review queue and change history
Join early access
Most teams

Growth

Up to 5 workspaces
up to 50,000 documents

  • Everything in Team
  • Daily scans and scanned-document extraction
  • Potential contradiction flags
  • Review deadlines and assigned tasks
Join early access

Enterprise

Unlimited workspaces
custom document volume

  • Everything in Growth
  • SSO and custom retention
  • Priority access to integrations
Talk to us

Company

Building infrastructure for enterprise AI knowledge.

Sourcewell is an infrastructure company building tools that help knowledge managers and AI engineering teams maintain clean, reliable, and up-to-date document libraries.

We focus on source quality — a critical problem where outdated or duplicated documents frequently lead to assistant hallucinations. Our goal is to make these transitions seamless, accountable, and easily searchable.

Sourcewell uses an AWS-first architecture to securely manage document data, AI comparisons, and issue tracking. We are working closely with pilot partners to validate our workflows before broader rollout.

Who we serve

  • Knowledge managers Review queues with assigned owners and deadlines.
  • AI engineering teams Cleaner retrieval sources and approved document records.
  • Support operations Catch macros that contradict policy before agents use them.

Get in touch

Team

Samuel Oladipo

Founder

Samuel leads Sourcewell's product vision. Drawing from experience managing enterprise knowledge systems, he built Sourcewell to eliminate the conflicting source documents that break AI assistants.

Fidelis Kami

Co-founder

Fidelis drives Sourcewell's technical architecture and AWS infrastructure. He designs the secure embedding, analysis, and orchestration systems that keep source records reliable and traceable.

Find the stale sources before your assistant does.

Bring one document collection. We’ll help you run your first scan and review queue.

Legal

Privacy Policy

Last updated: October 2026

What we collect

When you submit a pilot request, we collect your work email address. We use this information only to evaluate your request and follow up about a pilot. We do not sell or share it with third parties.

How we store it

Form submissions are stored securely on AWS infrastructure. We retain your contact information only as long as needed to manage the pilot conversation. You may request deletion at any time.

Changes to this policy

We may update this policy as the product and company develop. We will update the "Last updated" date when we do.

Contact

Questions about this policy: hello@sourcewell.ai

Legal

Terms of Use

Last updated: October 2026

Use of this site

This website provides information about Sourcewell's product and pilot program. The product preview uses entirely fictional documents, findings, and team members. No real commercial data is represented anywhere on this site.

Pilot program

Submitting a pilot request creates no contractual obligation on either side. Any engagement will be governed by a separate written agreement, signed before any work begins. That agreement will specify scope, data handling, and commercial terms.

Product preview and fictional data

The interactive preview uses entirely fictional document names, conflicts, and resolutions. It is intended only to illustrate how the product interface works. It does not represent actual customers or actual operational data.

Disclaimer of warranties

This site is provided as-is. Sourcewell makes no warranties — express or implied — about the completeness, accuracy, reliability, or availability of the information presented. We reserve the right to change, suspend, or discontinue the site at any time without notice.

Contact

Questions about these terms: hello@sourcewell.ai