SAMDAM Mission Partners designs secure, auditable AI and cloud systems for federal mission environments. Our flagship IP, Sourcine, treats the model as an untrusted component — facts come from authoritative records, not the model.
Critical systems are scanned for vulnerabilities monthly, as required by RA-5(2) and defined in the authorized SSP §3.11.
Findings from the deterministic-first research study — an observational production deployment within a bounded protected-field scope, not a controlled benchmark. SHA-256 audit verification recorded zero detected failures across all 10,000 artifacts. Sourcine productizes the architecture the study describes. See the study →
We build and secure mission systems end to end — from cloud architecture and RMF acceleration to AI that holds up under security, legal, and authorization review.
Production AI pipelines that automate NIST RMF assessment, control documentation, and vulnerability management — with deterministic validation gates that block AI-fabricated guidance.
Authorization-boundary design, IAM and KMS hierarchies, and STIG/CIS-hardened baselines for FedRAMP-authorized and air-gapped environments.
Traceability, control mapping, and OSCAL-ready evidence produced during delivery — cutting assessment timelines while strengthening the authorization package.
Source-bound retrieval, citation enforcement, fact/synthesis labeling, and tamper-evident audit trails — the controls that keep model output from reaching an operational decision unchecked.
A requirements-driven secure delivery and runtime assurance platform. Facts are bound to authorized sources before any model runs; the model may refine style, never author a fact, citation, or identifier.
In production today: PursuitGuard and Structured JSON Extractor — commercial products built on Sourcine.
Explore Sourcine →Turns plain-language mission needs into reviewable BRD/PRD/SRS/TDD and a candidate compliance framework before any build begins.
A security-gated delivery engine — six phases, six pass/fail gates. A failed gate blocks progression until it’s corrected or formally dispositioned.
Deterministic-first runtime for AI-assisted output: source binding, citation enforcement, fact/synthesis labeling, protected-field validation, and audit commit (G0–G5).
The architecture behind Sourcine, documented as a technical paper for the federal and regulated-industry community.
RAG reduces hallucination; it cannot eliminate it, because output formation stays stochastic. Deterministic-First inverts the flow — responses are composed programmatically from version-controlled authoritative sources before any optional LLM invocation, which is reduced to a constrained style-only refiner behind a fail-closed validation gate.
Twenty-five years architecting federal compliance automation, cloud security, and AI/ML systems for classified and air-gapped environments. He designs multi-agent AI pipelines deployed inside FedRAMP-authorized boundaries with zero external cloud-AI dependencies, and the deterministic validation gates that keep AI-fabricated guidance out of compliance work — the architecture now formalized as Sourcine. Prior program and engineering leadership spans the Intelligence Community (IC), U.S. Navy, and DoD.
We characterize your mission, data sources, query profile, and assurance requirements — then scope a pilot against an approved source set. No speculative AI, no compliance theater.