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Theory AI

From theory to practice.

Theory AI builds the data infrastructure that lets you deploy AI into your ecosystems: pipelines, ground truth, evaluation, and the operations underneath. Ten people, three languages, five client programs live. Headquartered in Washington, DC, with an international team delivering globally.

Trust and compliance

SOC 2 Type II
In process
SOC 1 Type I
In process
FedRAMP Moderate
In process
Data residency
US · EU · on-prem
Compliance detail →

Audits under way. No framework is claimed as achieved.

Why data

The distance between a pilot and production is data work.

A demonstration runs on curated data. Production runs on what the organization actually holds: inconsistent, unlabeled, ungoverned. Closing that distance is the work, and it is most of the work.

It is people work as much as engineering, so the people doing it are permanent employees rather than a task queue. The same team stays with the data as it matures, which is why quality holds after the first delivery.

What we do

Three things we deliver for clients

  • 01

    RAG pipelines

    Retrieval systems built on your own corpus: ingestion, chunking and embedding decisions per document class, index operations, and evaluation of what the system actually returns.

  • 02

    Model development

    Task definition, eval sets built from real traffic, fine-tuning and adaptation, red-teaming against domain failure modes, and monitoring for drift and cost once it is running.

  • 03

    Data annotation

    Human ground truth from permanent teams: annotation, transcription and multilingual review, with domain-expert QA measured per annotator rather than per batch.

How the engagement works

Who we serve

Where the data has to hold up

Engagement types we are built for, described by agency class rather than name.

  • Federal health agency

    Multilingual intake and case documentation, where the record has to be defensible as well as accurate.

  • DoD component

    Evaluation for decision support, including refusal behavior and the failure modes a review board will test.

  • Prime contractors

    Ground truth and data operations delivered inside an existing task order and its reporting cadence.

  • Commercial enterprise

    Retrieval and annotation on regulated internal corpora, with residency and access set per engagement.

Global delivery

Headquartered in DC, delivering worldwide

Theory AI is registered and led from Washington, DC, and operates globally. Our working day overlaps Europe, the Gulf and the US east coast. The team is international by design: we hire wherever the specialism is and train in-house.

Washington, DC HQ

Meet the team

Insights

Notes from the data layer

All insights →
  • Evaluation

    Your accuracy number is not an evaluation

    Aggregate scores hide the failure modes a review board actually cares about.

    July 2026 · 8 min read

  • Data operations

    Per-annotator quality beats per-batch QA

    Measuring people rather than batches is what makes a correction stick.

    June 2026 · 6 min read

  • Compliance

    Preparing for FedRAMP as a ten-person company

    What readiness costs in engineering time, and why we publish the status rather than the badge.

    May 2026 · 6 min read

For agencies and primes

Bring us the use case

Tell us what you are trying to deploy and what data you hold. We will tell you what is feasible, including when the answer is not yet.

Book a call