How JLAS-AI turns data into a decision.
JLAS sits between your authoritative systems and the person who decides. It structures one constrained decision, compares the feasible options and returns an explainable decision package.
Approved mission context
Resource state, demand, time, priorities and constraints from existing systems.
Feasible COA comparison
Constraint screening, modeled mission effect, margins and sensitivity.
Decision package
Preferred option, alternatives, risk, confidence and what would change the answer.
Human disposition
An authorized person approves, modifies or rejects. JLAS executes nothing.
The logistics problem has changed. Decision tools haven't kept up.
Contested logistics
Planners must assume disrupted networks, shrinking timelines and scarce lift. Decisions that once had days now have hours.
A layer, not a replacement
Organizations have invested heavily in data platforms. JLAS adds decision value on top of them instead of asking anyone to rip and replace.
Built by an operator
Founded by a 23-year U.S. Army logistics and mobility veteran with graduate-level computer science training. The product starts from the decision, not the data.
Where JLAS fits
| Capability | Dashboards & BI | ERP & systems of record | JLAS-AI |
|---|---|---|---|
| Shows current resource state | Yes | Yes | Consumes it |
| Enforces hard mission constraints | No | Partly | Yes |
| Generates and compares courses of action | No | No | Yes |
| Traces choices to mission effect | No | No | Yes |
| Shows what would change the answer | No | No | Yes |
| Replaces your system of record | — | — | No, by design |
An evidence-led path to deployment.
Each stage earns the next. We don't scale claims ahead of evidence.
Controlled demonstrator (TRL 4)
Constraint handling, COA comparison, decision boundaries, human disposition and evidence capture, proven on synthetic scenarios.
Sponsor evaluation
One bounded mission workflow, representative approved data and success measures agreed before testing.
Pilot
Integration with existing systems, deployment hardening and security evidence in the user's environment.
Transition & scale
Operational validation under the required authorization, then expansion to adjacent programs and dual-use markets.
Defense first. The same problem everywhere resources are scarce.
Defense & joint logistics
Sustainment, maintenance, repair parts and transport decisions tied to readiness.
Emergency management
Supply staging and distribution across concurrent incidents and disrupted networks.
Aviation MRO
Critical parts, maintenance queues and aircraft availability.
Critical infrastructure
Restoration priorities and asset allocation under disruption.
Adjacent markets are commercialization targets, not current customers or deployments.
Clear about what's proven.
We separate engineering evidence from operational validation. Here is exactly where JLAS-AI stands, so evaluators and investors can plan with confidence.
Bring us a bounded decision problem.
Government evaluators, primes, technology partners and investors each have a direct path to a briefing.