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sysparency

The Custom Code Intelligence Platform

Your software system, turned into a model people and AI can trust.

The platform reads the real source and the existing documentation of a system — however old, however large, in whatever language — and produces complete, source-cited documentation backed by a queryable knowledge graph.

Four capabilities, one spine

Every system passes through the same four capabilities — the reason the same product can describe a mainframe transaction and a modern web service in the same shape.

documentexplainrecommendtransform

Document

A living knowledge base of every screen, program, batch job, interface, table and field — regenerated from the code, never hand-maintained.

AIfactfactfactevery claim ← a cited fact

Explain

Human-readable narrative in business language, grounded strictly in the cited facts.

keeprefactorrebuildretiredisposition per component

Recommend

Evidence-backed transformation recommendations at system, module and artifact level — tuned to your declared goal.

one query · any question

Transform

A deterministic, machine-readable model AI agents can reason and act against, safely.

Navigate the system top-down

The documentation is an application you navigate — System → Module → Software Artifact → Code — opening with business summaries and growing more technical as you go deeper.

SystemModuleSoftware ArtifactCode

Read every artifact business → technical → implementation

A product owner reads the business value of a screen; an architect reads the call graph and complexity; an engineer reads the cited source. Same artifact, same source of truth.

1 artifactbusinessarchitectureengineeraudit

Business / functional

What it is for and the outcome it enables — rules, validations and calculations, in plain language.

one query · any question

Technical / architecture

Architectural role, call graph, interfaces, dependencies and structural complexity.

fact · cited · versionedfact · cited · versionedfact · cited · versioneddefensible & reproducible

Implementation / code

How the code actually works, beside the cited source — with code-health signals for duplicated, unused and embedded open-source code.

See the platform on your own system

A 30-minute demo on a representative slice of your code.

Editions

Go deeper by system type

SAP

SAP customers facing the 2027/2030 S/4HANA deadline must rationalise years of accreted custom code under time pressure. Sysparency turns that from an opinion-driven exercise into an evidence-driven one.

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Mainframe

Large mainframe and IBM i systems run the core business processes of banks, insurers and public institutions — and are barely understood. Sysparency reads the real source and makes the behaviour explicit, cited and queryable.

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Software

Custom Code Intelligence is not only for legacy. Modern stacks accumulate the same undocumented complexity — and the same key-person risk. Sysparency gives Java, Python and other systems the same documentation, graph and AI surface.

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FAQ

Straight answers.

  • Complete, navigable, source-cited documentation of a software system, a queryable knowledge graph, and an assistant that answers complex analytical questions. Every documented fact links back to the exact source it came from.

  • A general AI reads code and guesses — and hallucinates. Sysparency first extracts the system’s facts deterministically, with a citation on every fact, and only then has AI write explanations grounded in those facts. The AI explains; it never invents. Re-running on the same input yields the same output.

  • Yes. The deterministic core — the documentation structure, the knowledge graph and the query surface — works with no AI at all. AI enrichment is an opt-in you control. With it off, no AI request is ever made.

  • SAP, mainframe and modern software — across a broad, growing set of legacy and modern languages. The approach is language-agnostic: covering a new technology adds breadth without changing the rest.

  • Completeness is measured as recall against a manual inventory — the target is ≥95%, and the reference corpus measures 100%. Trust comes from provenance: every fact carries a citation, and every hidden dependency is explicitly flagged rather than silently omitted.

  • Enterprise single sign-on, encryption at rest, read-only access for the query layer, and an opt-in AI layer that can be kept EU-resident. The whole deterministic pipeline can also run fully on-premises and air-gapped — a proof of value can run before anything leaves your boundary.

  • The documentation is regenerated deterministically from the code on each upload, with caching so re-runs are cheap. Old versions remain available and any two can be compared — so the cost of staying current trends toward zero.

  • Book a 30-minute demo, ideally on a representative slice of your own code. We’ll show you the output and give you a straight answer on fit, timeline and the fastest path to value.