Are you ready for AI your whole company can actually trust?
Your AI can explain your whole industry but has no idea how your business runs. DearTech-OS gives it your company's own knowledge, so it finally answers like it works here.
- Answers grounded in how your business actually operates
- One shared layer your whole company's AI works from
- You can see where every answer came from
Our current cohort is full. Join the waitlist to be next.
Which sounds like you?
Two ways companies get here
You are a founder all-in on AI tools
You have Claude, ChatGPT, Cursor, the lot, but the context lives in individual chats, nothing compounds across the team, and you cannot tell which workflows actually work.
See how DearTech-OS fixes thatYou run a business that depends on you
Everything routes back through you and a couple of key people, the admin grows every time you do, and you cannot see how to grow without it just getting heavier.
See where your business standsSound Familiar?
Is your company context stuck in people and their individual workflows?
Your founder is the search engine
Everyone asks the same person where the latest deck, pricing logic, customer insight, or board narrative lives.
AI context is locked to one chat surface
Your AI tools have files attached and instructions written, but the knowledge cannot be searched as a graph, traversed across decisions, or used outside that one AI's chat.
Knowledge does not compound
A great customer call creates insight, but it dies in the transcript unless it gets linked to ICP, objections, product, and sales.
Context walks out the door
When a key operator leaves, their tacit knowledge, chat histories, and personal AI workflows leave with them.
Reports require archaeology
Investor updates, product decisions, and GTM planning still require hunting through old docs instead of querying one graph.
These are the patterns we see first when we map how a company actually runs.
The Shift
From scattered knowledge to an operating layer
Your own instance
A dedicated, isolated DearTech-OS instance, hosted and run by us (self-hosting on request). Your data is walled off from everyone else's.
Any AI tool
Claude, ChatGPT, Cursor, and future agents query the same graph through MCP. No new tool for your team to learn.
Yours to keep
Your knowledge lives in a git-backed graph you own, in portable markdown. Leave any vendor any time and it comes with you.
The Transformation
From static docs to compounding context
Before
- Critical knowledge scattered across docs, calls, decks, and chat
- AI knowledge locked inside one vendor's chat. Can't be searched as a graph or fed to other tools
- Investor updates rebuilt from scratch every month
- Customer insight disconnected from product and GTM decisions
- New hires onboarding through tribal knowledge and guesswork
After
- A living knowledge graph founders can see and traverse
- Source context, confidence, status, and relationships are visible
- AI retrieves the few concepts that matter for each question
- Every useful insight strengthens the rest of your graph
- GTM, finance, product, ops, and board reporting share context
Use Cases
Where shared context pays off
AI tools
Your AI tools start cold, so a useful answer means re-pasting the same product, customer, and GTM background every time.
Claude, ChatGPT, and Cursor answer from your own context, so useful work does not need re-explaining.
Reporting
Board updates and operating reviews mean hunting through old docs, decks, and threads every month.
Reporting pulls from one trusted layer instead of being rebuilt from scratch.
Onboarding
New hires and stand-ins learn the company by interrupting the people who already know.
They get up to speed from the graph, so context does not depend on who is in the room.
AI workflows
AI automations built on generic context miss how your company actually runs.
Build end-to-end workflows grounded in your operating context, and surface the optimisation wins scattered context keeps hidden.
How It Works
<your-company>-OS, powered by DearTech-OS
We stand up your own instance, connect it to the AI tools your team already uses, and get your knowledge in. You own the graph.
We stand up your instance
Your own isolated DearTech-OS instance, hosted and operated by us, with Google sign-in for your team and your data walled off from everyone else's. Self-hosting on request.
Connect the tools you already use
Claude, ChatGPT, Cursor, and other agents query it through MCP, so your team gets shared context without changing how they work.
Get your knowledge in
We map how your company actually runs into the graph, and the system keeps capturing and distilling new context as you work, so it compounds instead of going stale.
You own it
The graph is yours in portable markdown, in your own GitHub repo, with role-aware access and a maintenance rhythm so it stays useful after we hand over.
What You Get
- A live DearTech-OS instance your team uses from day one
- Shared context across the AI tools you already use
- Self-healing graph health and ingestion that run for you
- Role-aware access for your whole team, via Google sign-in
- Your graph in portable markdown you own
The Approach
Built as a product, not a project
DearTech-OS is the shared memory and context layer your company runs on, your own instance you connect to, not a one-off build that goes stale after handover.
Your own isolated instance
Every company gets a dedicated instance. Your data is never mixed with anyone else's, and you own the graph.
Works through your existing tools
Shared context shows up inside Claude, ChatGPT, and Cursor over MCP, so the whole team uses it without learning a new app.
It stays current on its own
The graph keeps capturing and distilling new context and self-heals stale or contradictory entries, so it compounds instead of filling with noise.
See what your company graph could look like
In a short call we'll map where your company knowledge lives, find the first slice worth putting in the graph, and show what your own DearTech-OS instance could look like.