Product
How Muninark works
Muninark is a Knowledge-Augmented Generation platform. It ingests the record a mature product leaves behind, builds a governed, temporal knowledge graph from it, and serves it back over the Model Context Protocol as cited, confidence-rated answers, to people and to AI systems alike. This page walks the whole path, from raw record to served answer.
The pipeline, end to end
Ingestion runs asynchronously through a multi-stage LLM pipeline; the answer path is synchronous, with no queue in it. Deliberately model-agnostic at both ends: the models can be swapped as the state of the art moves, and better models simply use the same graph better.
01 · SOURCES
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02 · LLM ENRICHMENT
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03 · THE SUBSTRATE
Temporal knowledge graph
entities · relationships · validity in time
Hybrid retrieval index
graph traversal · full-text · vector
Expert review portal
confirm · correct · on the record
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04 · SERVING · no queue in the answer path
Works where your team already works
Muninark is an MCP server. There is no separate chat app to adopt: your teams keep their tools, and the tools get your history.
Anatomy of an answer
Every answer is the same structured object, whether a person asked in Slack or an agent asked over MCP.
The question, as asked, kept with the answer for the audit trail.
Calibrated confidence. High, Medium, Low, or a refusal marked Insufficient.
Version scope. The release or date the answer holds for.
The answer, written from the assembled evidence alone.
The evidence pack. Typed citations: source system, record id, date.
v4 keeps dual rounding to honor the 2019 contract terms; the fallback was removed in v6.0 once migration completed, so v6 rounds once, at line level.
THE CONFIDENCE SCALE
Below 30%, Muninark declines to answer rather than guess. Insufficient is a designed answer: a system that admits what it does not know is one you can trust in the cases where it does.
It knows what was true, and when
Facts carry temporal validity. When your customers run different versions at once, one question has several true answers, and Muninark keeps every one of them, dated.
Superseded facts stay on the ledger. Ask as of v4.8 and the first row answers; ask today and the second one does.
Who Muninark is for
Most of what a mature product knows about itself is not in the current source. It is in the record of how the product came to be. These are the people who need that record.
Teams inheriting a legacy system
The code still runs, but the reasons behind it left with the people who wrote it. Muninark recovers those reasons from what they did write down, all dated and cited.
Investors and acquirers in due diligence
Knowing the code together with the history of its creation is worth more than its latest version. Muninark turns that history into evidence an outside party can query.
Vendors whose customers run different versions
Your v4 customer and your v6 customer ask the same question and need different answers. Muninark answers as of the version in front of the support engineer.
Engineering teams in regulated industries
An auditor asks which change implements clause 4.2. Muninark traces requirements to the decisions and commits behind them; where the trail is incomplete, it answers Insufficient.
Teams refactoring or rewriting old code
A rewrite fails on the behaviors nobody knew were load-bearing. Muninark tells you which quirks are contractual obligations and which are accidents of history, scopes a partial refactor through impact analysis, and checks that the new code still honors the recorded decisions.
Organizations losing context to turnover
Every departure takes context. Muninark keeps the answers with their sources, so new engineers ask the graph and senior engineers stop serving as the search index.
Nine kinds of questions it is built to answer
Historical why
Trace decisions back through the commits, tickets, and discussions that shaped them.
Impact analysis
Follow a change through the modules, contracts, and versions it touches.
Change conformance
Compare what was agreed with what was shipped.
Knowledge discovery
Surface prior art and past attempts before anyone repeats them.
Onboarding
Give new engineers grounded, cited answers from day one.
Archaeology
Recover the story behind artifacts nobody remembers writing.
Risk and ownership
Find single points of failure before they resign.
Deployment context
Answer from production and deployment records, not from memory and assumption.
Regulatory tracing
Trace requirements to the commits and decisions that implement them.
Governed by design
Institutional memory includes things not everyone should see. Access control is a property of the platform, not a feature request.
AUDIT TRAIL · EXCERPT
SAMPLE ENTRIES · each links to its question, evidence, and hash-chain position
How it is delivered
Licensed enterprise software, installed in your environment: the engine, the MCP server, an ops console, and a review portal where your experts curate the graph. Built for organizations with mature products and real compliance obligations; there is no self-serve sign-up, everything starts with a conversation about your product.