Products
Software we own and license: decision support, forecasting and workflow products built for the missions our clients already run.
Strategic Resources, Inc. · AI venture · est. 2026
Intelligence,
engineered
for the mission.
SRI AI takes an artificial-intelligence capability from first measurement to an accredited system in production, and stays to run it. Federal and commercial. Evidence over demonstration.
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- CMMIMaturity Level 3
- ISO9001 · 20000-1 · 27001
- 30+years delivering to government
Six ways in
Whatever the entry point, the end state is the same: a system that is measured, accredited and operated.
Solutions
AI fitted to one client's problem and data, from the first measurement through a pilot with pass rules written down in advance.
Engineering
Pipelines, models, evaluation and the secure infrastructure around them, built to run inside an accredited enclave and to be audited.
Services
Operating what we build. Monitoring, retraining, model governance and the human review that keeps an automated system accountable.
Consultation
Plain answers to hard questions: what AI can and cannot do for a program, what it would cost, and how to prove it before anyone depends on it.
Innovation
Applied research with partners and clients, and the discipline to tell a real result from a demonstration.
The method
- 01
Measure before you model
Every claim is typed by its evidence, from simulation to live results, and never ranked above its rung. A result on real data outranks a polished demonstration.
- 02
People decide
Systems recommend and explain. A named person approves, and every automated action is logged against the authority that allowed it.
- 03
Built for accreditation
Data stays in the client's enclave. Models are chosen for provenance as well as performance. The work inherits SRI's CMMI Level 3 and ISO process.
- 04
Operated, not handed off
We stay. Monitoring, retraining and governance are part of the delivery, so the system is still right a year after it went live.
Bring us the decision
Tell us the problem, the data you have, and the decision it should improve. We answer with what we think is possible and what it would take to find out.