Your AI agents can reach your data. They still can't use it.
A single Gmail API response is 847 tokens. What your agent actually needs is 127. The other 720 are X-Gm-Message-State headers, base64 encoding, and nested JSON nobody reads. Multiply that by 50,000 emails. Your model is burned out before it starts thinking.
The industry's answer is retrieval. Embed documents, search at query time, stuff fragments into context windows, and hope the model assembles meaning. This is the computational equivalent of interpreting source code on every run instead of compiling it once.
It doesn't scale. It doesn't understand. It just guesses.
Context is a compilation problem.
We compile raw data into structured intelligence—contact graphs, decision traces, sentiment trajectories—before the agent ever runs. Not retrieved fragments. Pre-synthesized understanding.
The interface is SQL. Standard Postgres. No proprietary SDKs, no vector stores, no new query languages. One query. Exact data. The format LLMs reason best in.
The query layer.
Unifies data from any source—email, CRM, messaging, browsing—into a single Postgres database. Agents query it with standard SQL. Per-source connectors optimize every data model to be LLM-first. Token-efficient representations, clean schemas, no junk headers.
The intelligence layer.
Raw data is noise. Compilers transform it into compiled outputs: contact profiles, relationship maps, decision traces. The compilers can use LLM agents as the reasoning step. query + write gives you dbt. query + run_agent + write gives you something new.
The comprehension engine.
Processes datasets two orders of magnitude beyond any context window. Recursively decomposes, examines, and synthesizes. Discovers what's relevant rather than waiting to be told. RAG gives you search results. ContextAgent gives you understanding.
Your personal data vault.
Soma compiles your email, calendar, messages, and browsing history into structured, queryable tables on your machine. It surfaces the patterns you miss—who you're neglecting, what's slipping, where your time actually goes.
Local-first. No cloud. No account. Every AI agent you connect gets context that makes it feel like it actually knows you.
Soma was the proof. The stack is the infrastructure.
Applied research for high-performance AI agents.
We're experimenters and tinkerers. We think context is a compilation problem, and we built the tools to prove it. We sell the infrastructure. We use it ourselves.