The enterprise context engine

Give every AI the
right context.

Your team already reads, highlights, discusses, and decides all over the web. Kontxt turns those signals into permission‑aware memory — then decides what each AI is allowed to see, and what it needs, for the task at hand.

Free for individualsOne line to deployNever trains anyone else’s model

Animated illustration: a sentence on a web page is selected, highlighted with Kontxt, saved as a memory, and an AI chat answers a question by citing that highlight.

1line of JavaScript to deploy
4systems — acquire, govern, select, deliver
works on any page you read
0of your data trains other models
Trusted by teams atCornellStanfordMichigan+ Fortune Global 500 companies
How it works

One engine between your people and every AI.

Model-agnostic. Agent-agnostic. Kontxt sits above your AI stack and decides what flows through.

Signals in — everywhere your team reads
In the browser today — no integration needed
Web pagesPDFsDocs & wikisDashboardsDiscussions
Native connectors · roadmap
SlackDriveConfluence
Kontxt · enterprise context engine
01Acquire

Highlights, notes, tags — plus the passive trail of what your team reads.

02Govern

Identity, permissions & provenance on every record — shared like a Google Doc.

03Select

Ranks everything you’re allowed to see; keeps only what the task needs.

04Deliver

MCP & API hand each agent its slice — citations attached.

ChatGPTClaudeCopilotCursorYour agents
Context out — any model, any agent
Why it’s different

A highlight isn’t a note. It’s a record.

Tools store documents. Kontxt records what your people decided mattered.

Ana highlighted thisEngineering · Research

The MLOps Blueprint: shipping models that survive production

research.acme.com · Ari Chawla

Most teams underestimate the rollout phase. The highest-risk window is the first 72 hours after deploy, when drift is invisible and rollback plans go untested.

One governed, machine-readable record
whoAna Kimura · Research
passage“The highest-risk window is the first 72 hours after deploy…”
sourceresearch.acme.com/mlops-blueprint
sharedrevenue-team · can view
tagsmlops · deploy-risk
discussed2 comments · J. Rivera, M. Tan
capturedAug 4, 2026 · 14:22 UTC
= one memory any permitted agent can retrieve — and cite

Multiply by every page your team reads. That accumulating, permissioned record of what your organization pays attention to is what other memory stores lack — and what Kontxt delivers.

For developers

One call. The right slice. Nothing more.

Ranked hybrid retrieval, scoped by the same permissions that guard the app — and every block says why it was supplied.

native MCPranked retrievalpermission-scopedauditable “why”
api.kontxt.io/mcp
REQUESTPOST /mcp
Authorization: Bearer <token>

{ "tool": "get_memory_blocks",
  "query": "what drove Q3 churn?" }
RESPONSE · RANKED · ACL-FILTERED
churn-postmortem.acme.com
highlight · shared: revenue-teamwhy: flagged by your team · high importance · 2d old
Q3 board notes — pricing
document · folder: strategywhy: same project folder · discussed by 3 people
only what this user & their teams can see
Permissions that travel

One access model on every surface — app, overlay, and API.

Private by default

Nothing is public unless you make it public.

Auditable

See what knowledge gets read, shared, and used — per page, per team.

Stop re-explaining your world to every AI.

Your first memory is one highlight away.

Free for individuals · No credit card · One line to deploy

The enterprise context engine — Kontxt turns what your people read, discuss, and decide into governed memory, and gives every AI exactly the context it’s allowed.
© 2026 Kontxt, Inc.Made for teams who read the web for a living.
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