Shared operating discipline
Knowledge, review, planning, reusable representations, continuity, work capture and mathematical foundations.
ARCHITECTURE
A foundation around
models and applications.
HSDLG’s Epistemic OS is a governance and application layer. It is designed to make the basis, boundaries and history of AI-assisted work inspectable.
APPLICATIONS
Domain work keeps its own responsibilities.
Geological exploration · Evidence assessment · Completed-work evaluation · Future applications
Reviewable analytical standards
Contracts for problem framing, evidence, uncertainty, qualification and use of supported methods.
Scoped local implementations
Analytical computation and routing with declared input profiles, limits and integration requirements.
MODELS & TOOLS
Bring Your Own Intelligence.
Choose the intelligence for the task. Retain the evidence and reviewed context that belong to the work.
This is an architectural overview. It does not depict a fully integrated production deployment.
WHY AN EPISTEMIC OS?
Work needs more
than an answer.
A model supplies reasoning and generation. Applications bring their domain knowledge and operating responsibilities. HSDLG is designed to connect those contributions to evidence, review, constraints and retained decisions.
Its APIs provide intended connection points for applications and future capabilities. A shared foundation can support different kinds of work without treating every domain as the same problem.
Deterministic checks address declared structures, calculations or rules. Scientific meaning, source adequacy and consequential judgment still need appropriate evidence and accountable assessment.
INSIDE THE FOUNDATION
Eleven areas of responsibility.
01–03
Knowledge, governance and theory
Acquire and preserve evidence. Govern review and adoption. Retain explanations and their lineage.
04–07
Reusable representations
Discover and govern primitives and higher-level patterns with applicability and change history.
08
Continuity
Reconstruct selected work while retaining constraints, corrections and unresolved conditions.
09
Tools and shared services
Frame tasks, plan method use and connect selected shared capabilities.
10
Work capture
Organize the records that allow earlier work to be examined and continued.
11
Mathematical foundations
Apply supported state, resource, ordering and history checks within declared models.
CURRENT STATE
Implemented components.
A clear next integration milestone.
Founder-led delivery
HSDLG methods support defined reviews and analytical work. Current capability access is internal. Selected components and applications have local implementations and tests.
Discuss a scoped engagementReliable MCP delivery
Complete and qualify the full Model Context Protocol path, selected client connections and operating controls. A local MCP component is one part of that path.
See component boundariesA model-flexible foundation
Support applications that reuse reviewed knowledge, corrections and operating discipline across their chosen AI models.
Explore the methodThe founder reports prototype use with Claude and Gemini, with more limited Grok and local-model use, including Gemma. This is prototype history, not universal compatibility or comparative performance evidence.