Software Engineering & AI · Veteran-Owned · Tampa, FL
Thorium Development Group de-risks software and AI builds the way engineers de-risk anything: name the make-or-break hurdles, clear the riskiest one first, and let evidence — not optimism — decide whether to proceed. AI-accelerated development makes each gate fast and cheap. 20+ years of software engineering, principal-led, with production AI systems running in daily use today.
The Gate Discipline
Before anything is built, we identify the assumptions that kill the project if they are wrong — extraction accuracy on your documents, latency at your volumes, an integration nobody has proven.
A working prototype against your real data, in days not quarters — AI-accelerated development makes the experiment cheap.
Gate passes → build with confidence. Gate fails → you just saved the budget. Either result is a win
Proof
Every number below is a real engagement moment — a gate cleared, a production failure diagnosed, a budget saved. Anonymized, but not hypothetical.
A govcon staffing firm needed candidate submissions automated. Before building the platform, we proved extraction accuracy on their real documents in week one. It passed — the system has run in production ever since.
An LLM pipeline hung for 36 minutes with no error and no log. Per-class timeouts and heartbeats now catch it in seconds.
Read the post →We benchmarked the standard vector-search stack against an LLM-built index on 2,000 capability statements. A top-25 shortlist surfaced 32% of truly qualified suppliers vs. 99% — and “we do NOT offer this” errors fell from 64% to ~0.
Read the post →Self-funded feasibility on Navy technical manuals: recovering content from degraded scanned pages, measured against born-digital ground truth — 99.3% word accuracy, 99.9% recall on safety content, every element carrying byte-exact provenance.
Services
LLM integration, prompt engineering, and AI-assisted development workflows that actually work in production.
Governance frameworks, constraint enforcement, and audit trails for AI-assisted development.
ETL pipelines, vector databases, and data preparation for retrieval-augmented generation at scale.
Smart contract architecture, DeFi protocol design, and decentralized infrastructure engineering.
System design, scalable backends, and data-intensive application architecture.
Cloud architecture, CI/CD pipelines, containerization, and infrastructure automation.
Technical leadership, engineering strategy, and team scaling for companies that need senior guidance without a full-time hire.
Expertise
Distributed tracing for agent workflows, per-class timeouts, failing loud, and the instrumentation that makes non-deterministic AI systems debuggable in production.
25+ years designing backend systems that process large volumes of data. System design, scaling strategy, and the architectural decisions that compound.
Taming the LLM spend and latency blowups that surface at scale — metering baked into the client, right-sized models, and moving inference off the hot path where it doesn't belong.
Principal engineer, tech lead, and CTO experience across defense contracting and enterprise software. We build your team's capability, not a consulting dependency.
From the Blog
We benchmarked the standard vector-search stack against an OKF index — Google's new standard for LLM-built knowledge bases — on a matching problem: 50 part specs, 2,000 supplier capability statements, and one job — find every shop that qualifies. The standard stack missed most of them, and no tuning fixed it. Here's why, with numbers.
A production post-mortem on an AI scoring step that failed, fell back to a worse path, and reported success anyway — why a single overloaded return value hides real failures, and the fail-loud discipline that catches them.
A production post-mortem on an LLM job that silently stalled for 36 minutes — why inherited SDK timeouts are dangerous, why AI calls come in latency classes, and the per-class timeout and heartbeat pattern that fixes it.
A 30-minute strategy call to discuss your current technical needs and whether an engagement makes sense. No pitch deck. No sales pressure.