Leaders
Keep decisions, relationships, and operating knowledge usable across the company, not locked in one person’s head or inbox.
How it works
Put your company’s context to work.
Corridor Context gives every AI your team uses the same private memory of your business. Here is how we get you there, from the first meeting to work that runs in hours.
Step 01
Align on the north star
We start as a partner to your leadership and agree on what the business has to achieve, then sit with the people doing the work and listen before we build anything.
Priority map
1Source more deals
- Use caseFind the owner behind every property
- ContextDeal and property history in one place
- EnablementOffice hours with the investments team
2Make real-time inventory decisions
- Use caseAsk live unit and pricing data in plain English
- ContextYour SQL data, connected through the gateway and mapped to your ontology
- EnablementShared skills for leasing and asset teams
3Close the books faster
- Use caseMonth-end close across every property
- ContextEvery SOP and lender requirement on file
- EnablementYour accounting team builds its own tools
Illustrative example.
Step 02
Your own instance
We set up an environment for your company alone: its own server, storage, database, and sign-in. Your team starts on a context layer that is ready to connect.
Your instance
Provisioned for your company alone
Gateway, the only way in
- Server
- Storage
- Database
- Sign-in
Permissioned access
Your AI reaches only your company’s context. Enforced in code, not policy.
Credentials stay put
Your sign-in tokens live only in the gateway. Product servers never receive them.
Access you can verify
Every AI tool call is logged as proof of access, without recording what you asked.
Step 03
Connect once and start building
Each person spends 10 minutes telling it their priorities, projects, and key people, then connects their meetings and the AI tools they already use. Context gathers as the work happens, so nobody re-explains the business.
- Properties12
- SOPs18
- People9
- Learnings27
Step 04
Every AI reads it
Claude, ChatGPT, Gemini, and Copilot all read from the same brain. Switch models whenever you want; what your company knows stays with you.
- Claude
- ChatGPT
- Gemini
- Copilot
Step 05
Turn the context layer on
Four weeks in, we sit down with your leaders to review what the context shows and pick the next workflows to build. Office hours, shared skills, and deployed engineering carry the work from there.
01Context
Context accrues on its own
Every meeting and conversation your team already has, gathered as the work happens.
02Data
The problems worth solving surface
Context surfaces the business problems most worth solving, ranked by the hours the work actually takes.
03Tools
Both teams build the solution
Your people bring the problem, our engineers ship against context that already exists, and what gets built lands on one shared layer.
Context, data, and tools turn multi-day work into hours.
From context to outcomes
The product gathers context. Your team turns it into how the business works.
Enablement
We get your team fluent.
Strategy, training, and adoption, led by our team inside yours.
Deployed engineering
We build it with you.
Our engineers work beside your team to co-build the agents and apps your work needs.
Built for individuals and teams who need AI to understand their world.
Teams
Work with AI that already understands the project. No rebuilding the same background in every chat.
Individuals
Your judgment, your shorthand, your open threads. Every conversation picks up where the last one ended.
What it is
What is context?
Context is everything your AI would need to know to do your job the way you do it: who decides what, what changed last quarter and why, and how the work gets done at your company. It lives in your head, your inbox, and your meetings. The model already knows the world. It does not know your company, and that gap is context.
How is this different from Copilot or ChatGPT Enterprise?
Copilot and ChatGPT Enterprise are assistants; Corridor Context is the memory underneath them. Your company’s context sits in a layer you own, and Claude, ChatGPT, Gemini, and Copilot all read the same brain through MCP. Switch models tomorrow and the context stays. We also put engineers inside your business to turn that context into workflows that run.
How is this different from a Markdown second brain?
A Markdown second brain works well for one AI-savvy person with time to maintain their files. It gets harder with more users, secure storage, upkeep, and keeping context current. Corridor’s founders started with pure Markdown brains and built this product to scale. Corridor Context uses the same approach, AI agents working over current Markdown, rebuilt for the enterprise: automatic integrations, team and company brain permissions, admin approvals, secure data, and an MCP gateway.
Can’t our team just build this?
You can, and we started there. The files are the easy part. The work is capturing every meeting, keeping personal brains private, holding shared knowledge until an admin approves it, giving each company its own environment, and routing every AI through one gateway with access enforced in code. Our deployed engineers build that alongside your team.
Does it replace our experts?
No. It puts their judgment to work in the decisions they aren’t in. Every line shows where it came from. The experts are the source; the brain makes their judgment count for more.
Your data
Who can see what?
Each person’s brain is private to them. Team and company brains hold only what someone proposes and an admin approves. Nothing moves on its own. Meeting records are visible to the people in the meeting and approved admins, and you can share them with teammates anytime.
What if it gets something wrong?
It can’t add to a team or company brain on its own. Every suggestion waits for an admin to approve it, and approved knowledge can be corrected.
Does it record every meeting?
It joins the calls on your calendar that have a Teams, Zoom, or Google Meet link, unless you switch that off. Each person can turn it off and invite the notetaker only to the meetings they choose, and your admin sets the default for everyone. It can post an intro message in the meeting chat when it joins. Before anything is saved, a filter removes sensitive identifiers.
Is it secure?
Yes. Your company gets its own environment: its own server, storage, database, and sign-in. Access is enforced in code, and every AI tool call is logged without recording what was asked. Account numbers, credentials, and similar identifiers are redacted before anything is stored. Our security program follows the SOC 2 framework.
Who hosts the data? Can we run it on-prem?
Corridor hosts, maintains, and secures your data as part of the platform license. Enterprise customers can also choose on-prem deployment.
Getting started
What does it connect to?
Corridor Capture, your own enterprise-grade notetaker, joins Teams, Zoom, and Google Meet calls. It turns each call into a transcript and a summary and writes them straight into each person’s brain. Outlook calendar connects through Microsoft sign-in, so the notetaker knows which meetings to join. Hardware recorders connect too, and our engineers can connect other sources, like email, on request. Every AI tool that speaks MCP, the open standard for plugging AI into other apps, can read the brain. Think of it as USB-C for AI. Through Claude or ChatGPT, it can also work with their other connectors.
What does our IT team have to do?
Very little. Your people sign in with their Microsoft work accounts, and the calendar permission is read-only and covers meeting details like titles, times, and participants. IT approves the Corridor Context connector in your AI tools’ admin settings and adds our domain to the approved list. We set up the server, database, and notetaker.
Do you train our people?
Yes. We start with leadership to align on the north star, onboard each person, then our deployed engineers build alongside your team.
What is deployed engineering?
Our engineers work inside your business, beside your team. They take the priorities from the north star, build the skills, agents, and workflows against your context, and hand them to your people to run.
How fast do we see results?
Right away. After a 10-minute onboarding, each person sees AI reason over their own context and take on their workflows. Four weeks in, the context compounds, and teams start building their own skills and workflows to get more out of AI.
How is it priced?
The software is a per-seat license. Services are billed as deployment or implementation packages, plus ongoing training and upskilling.
Start building your context layer today.
Bring the meeting, handoff, or decision trail your AI keeps missing. We’ll map the knowledge behind the work and define a focused first rollout.