Sustainment AI Platform
Fault Isolation in Seconds. Cited to the Source.
Implicit captures knowledge in a cited, searchable workspace so every maintainer can be an expert.
Implicit's AI is built on a graph-powered architecture that turns technical orders, bulletins, and fault logs into structured knowledge. Ask questions in plain language and get source-grounded fixes in seconds.
Hybrid delivery: second-brain knowledge bases for humans, MCP server access for external AI agents — isolated workspaces keep context clean.
TOs, bulletins, fault logs, AARs — every format, ingested and structured.
Entities and relationships modeled into a versioned knowledge graph.
Agentic GraphRAG understands intent and returns source-cited answers across knowledge checks, support, writing, and summarization.
Prebuilt learning templates for practice, comprehension, explanation, reflection, and retention — tuned to maintenance workflows.
> QUERY
"Why is the #2 hydraulic pressure dropping after engine start on tail 6128?"
Implicit Response
Likely cause: degraded check valve in the #2 EDP return line. Inspect per TO 1F-16C-2-49JG-00-1, §3.4.2 before isolating EDP. Recent service bulletin SB-2024-117 supersedes prior torque spec.
[ Status: Legacy ]
Maintenance knowledge fragmented across systems, binders, and the heads of your most experienced personnel.
// Preview: All sources and knowledge loaded in one place.
[ Status: Volatile ]
Institutional knowledge walks when experienced maintainers rotate or separate.
// Preview: Access past sessions for education and context.
[ Status: Variable ]
Troubleshooting speed determined by who's on shift, not what's in the documentation.
// Preview: Inline citations allow instant access to source documentation.
[ Status: Analog ]
Manual, inconsistent work logs that don't survive the next inspection cycle.
// Preview: Generate Shift Logs to keep all maintainers informed.
[ Status: Reactive ]
New maintainers spend months building proficiency through trial and experience.
// Preview: Generate learning and training content on any topic.
It's not a chatbot bolted onto a search index. It's a graph-powered reasoning layer where every answer is cited to its source. Built for environments where verifiable accuracy is the standard.
Plain-English answers, cited to the page.
Symptom-to-fix in seconds, at the jet.
Containerized. DDIL-native. ATO-ready.
We'll walk your team through a live demonstration on representative documentation, review your sustainment workflow, and outline a path to pilot — including transition via PEO-TIS and ASGARD.
