Collect through workflows.
Use data-collection workflows to bring information into the platform while retaining the source context and provenance needed downstream.
THE SHARED KNOWLEDGE & QUESTION-ANSWERING FOUNDATION
Minsky Platform combines data-collection workflows, a knowledge base, private and public knowledge graphs, domain ontology, and question answering. Heavy reliance on grounding connects answers to the underlying knowledge and source evidence, with hallucination-free answers as the design goal. It is available on AWS Commercial Cloud and GovCloud, and it sits inside Minsky One.
MINSKY PLATFORM / THE ARCHITECTURE
Data-collection workflows bring in the evidence. Mission Memory brings the human perspective: knowledge, opinions, experience, intuition, and team expertise.
Together, they shape domain ontology and connected knowledge, giving grounded question answering the context of your mission.
The M3 vision: scale experts through digital twins that augment rather than replace, provide grounded answers, and build mission-specific ontologies in minutes.
Mission Memory across every layer.
Report R-17: “Project Atlas tested a coastal sensor in June.” The collection workflow retains the report and its source reference.
M3 context: the expert’s mission is coastal monitoring.
Use data-collection workflows to bring information into the platform while retaining the source context and provenance needed downstream.
Organize collected information in a knowledge base that supports the solution’s analysis and question-answering needs.
Represent entities and relationships in private and public knowledge graphs, keeping information connected to its context and evidence. Define who can see what in that graph, down to the individual fact, including personally identifiable information (PII). In intelligence use cases, that permissioning decides which person and which knowledge is visible.
Concepts, entity types, and relationships come from the mission’s evidence, so each solution can organize its knowledge without a separate modeling engagement.
05 / GROUNDED QUESTION ANSWERING
Minsky Platform’s question-answering layer relies heavily on grounding in the knowledge base, knowledge graphs, domain ontology, and source evidence. The design goal is hallucination-free answers: responses whose basis can be traced and evaluated by the people using them.
MINSKY PLATFORM / MISSION MEMORY · M3
Minsky Mission Memory - M3 - is about you and how you see the world. Your knowledge, opinions, experience, and intuition. Your team.
You are not tokens. You don’t rely on tokens in a fight. You rely on humans and their expertise.
We model the world and your expertise in it. Evidence-first, not AI-first. AI is a shovel. You hold the map.
THE M3 VISION / THREE FOUNDATIONAL TECHNICAL GOALS
Digital twins that augment, not replace.
Evidence as the foundation for answers.
Create a data-driven ontology, from the evidence you already have, without waiting for forward-deployed engineers.
MISSION SOLUTIONS / PART OF MINSKY ONE
Intelligence Production Environment
Accelerate the intelligence lifecycle.
From requirement to decision.
Search, draft, check, and publish in one workspace, with claims tied to sources and tradecraft checks while you write.
Science & Technology Investment Outcomes
Accelerate defense R&D decisions.
With trusted knowledge.
Transform disconnected research, budgetary, and contractual artifacts into a continuously updated knowledge graph that supports faster, evidence-backed decisions.
SUPPORTING AI LAYERS
Contact us to describe your use case. We’ll show you how Minsky can solve it today.