A read on where AI fits in the Archaius stack. And where a database fits better.
The Signals Assurance Layer is in the field. GRALE C2 ran through Falcon Peak 2025 at Eglin with JIATF 401. GRALE GPS and TALON carry their own customer lines. An SF-veteran CEO, a founder chief scientist, a PhD research team, and a public commitment to the small-SWaP anti-jam slot. This page is a short note on what we saw and the first conversation we would like to have.
Most organizations automate the wrong things.
About 60% of what a defense-tech company does every day is traditional code and database work. About 30% is rule-based logic. Around 10% is a real AI problem. The work is sorting those three into the right layers before anything is built.
Applied to Archaius, the map resolves quickly. Capture libraries, SEPA interoperability documentation, field-test artifacts, and three product-line release histories are database and code problems. ITAR gating, CMMC 2.0 evidence routing, ATO package assembly, and customer-permissioning on GRALE imagery are rule-based logic. ML for spectrum sensing and emitter classification is the 10%.
A layered context architecture over the first two gives the engineering team its R&D cycles back and gives the Archaius capture team a posture that travels.
We built a multi-agent compliance platform for a mining-sector client operating under DRC regulatory flowdowns. One hundred sixty plus hours of compliance work per cycle collapsed to under five minutes. The shape is identical to Archaius capture, ATO, and interoperability workflows: high document volume, repeat structure, real penalty for getting it wrong.
- Regulatory flowdown agentATO evidence orchestration across three products
- Compliance narrative generatorSBIR and SOF capture proposal library
- Audit-ready document chainSEPA interoperability traceability for program managers
The methodology is published.
Interpretable Context Methodology: Folder Structure as Agent Architecture, submitted to ACM TiiS. The core idea is that agent context can be organized as a layered filesystem with measurable gains in interpretability and reproducibility. Open source under MIT license.
Repogithub.com/RinDig/Interpretable-Context-Methodology-ICM-
Who is on the other side of the table.
- 01Jake Van Clief, founder. Marine Corps veteran, eight years. Cryptographic systems. F-35 and F-18 avionics.
- 02MSc Future Governance, University of Edinburgh. Published in ACM TiiS (ICM) and arXiv (Ethics Engine, arXiv:2510.11742).
- 031,500+ enterprise learners trained since May 2025 across Correlation One (Pacific Life, Colgate-Palmolive) and KPMG UK, one of the Big Four.
- 04Eduba partners with NLP Logix for work that sits below the orchestration layer. NLP Logix has been in machine learning since 2011 and runs over 150 data scientists.
Thirty minutes with Matt.
Bring the Falcon Peak after-action and the last SBIR response you shipped. We walk the 60 / 30 / 10 map live and scope the first sprint from there.
If the conversation lands somewhere else, Matt will say so on the call.