Services
Build the company knowledge layer your AI tools are missing
DearTech-OS services turn scattered company knowledge into operating infrastructure: a living graph your team can query, maintain, and expand across GTM, finance, product, reporting, and operations.
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Service Areas
Start where shared context will unlock the most leverage
DearTech-OS Foundation
The first company knowledge graph layer: context audit, source standards, navigation, ingestion workflow, and handover.
Best for
Founders who know company knowledge is scattered but need a focused starting point.
GTM Context Layer
Connect ICP, positioning, buyer pains, objections, sales learnings, proposals, and campaign context so GTM knowledge compounds.
Best for
Teams using AI for sales or marketing but constantly re-explaining the same context.
Finance and Reporting Context
Structure the knowledge behind investor updates, operating metrics, risks, assumptions, and board preparation.
Best for
Founders rebuilding the same reporting context every month.
Product and Customer Context
Link customer conversations, feature requests, roadmap rationale, support patterns, and product decisions.
Best for
Teams where product knowledge is split between calls, tickets, docs, and memory.
Process
A practical build, not a strategy deck
Your team leaves with a working operating layer and a clear rhythm for keeping it useful.
Audit
Map where knowledge lives, who people ask when they cannot find it, and which workflows lose the most context.
Architect
Choose the first operating area, define the graph shape, and set simple standards for sources, status, and ownership.
Build
Create the knowledge graph, navigation layer, ingestion flow, and operating documents your team can use.
Handover
Train the team, document the maintenance rhythm, and leave you with a system that can keep improving.
Deliverables
What a typical engagement leaves behind
FAQ
Common questions about DearTech-OS
What is DearTech-OS?
DearTech-OS is a Context OS for founder-operators. It turns scattered company knowledge into a living graph that AI tools and teams can query across GTM, finance, product, reporting, and operations.
Who is DearTech-OS built for?
Seed to Series A founder-operators whose AI knowledge lives inside one vendor's chat surface (Claude, ChatGPT, etc.) and cannot be searched as a graph, traversed across decisions, or used outside that AI's chat. It is built for teams where operating knowledge currently lives in scattered docs, calls, and individual heads.
How is DearTech-OS different from Claude Projects, Notion AI, or a custom GPT?
Claude Projects (even on Team or Enterprise) work only inside Claude's chat surface. Files are attached, not searchable as a graph. Notion stores files behind a cloud API. DearTech-OS keeps markdown files canonical on disk and adds a typed knowledge graph plus MCP server on top, so AI tools can search, traverse, and query the graph from Claude, ChatGPT, Cursor, or any MCP-compatible tool, and the knowledge can feed dashboards, reports, and agents beyond chat.
Where does a DearTech-OS build usually start?
Most builds start with one high-value operating area, such as GTM knowledge, investor reporting, product and customer context, founder operations, or team onboarding. The first layer proves value before expanding.
Do you replace our current tools?
No. DearTech-OS is designed to make existing knowledge more usable. It works alongside docs, CRMs, call transcripts, product tools, and AI tools rather than replacing them.
Can non-technical teammates use DearTech-OS without learning git?
Yes. Non-technical teammates query the knowledge graph through Claude, ChatGPT, or any AI tool by asking questions in plain English. They never touch git, markdown, or files directly. Role-based access (viewer, maintainer, admin) controls what each teammate can see or change.
How long does a DearTech-OS engagement take?
A foundation engagement typically runs four to eight weeks, from initial audit to team handover. Expansion into additional operating areas happens after the first layer is in active use.
What do we own after the engagement?
You own your company knowledge layer, the operating documents, and the handover materials. A DearTech-OS engagement is built for usable infrastructure and team ownership, not consultant dependency.
No client data lock-in
Your company knowledge stays yours. The system is designed around ownership and portability.
Source-grounded by design
Important context carries enough source and status information for the team to trust it.
AI tool agnostic
The knowledge layer should outlive whichever AI client your team uses this quarter.
Start with a context audit
In 30 minutes, we can map where your operating knowledge is scattered today and identify the first DearTech-OS layer worth building.
Let's chat