KnowledgeOps Platform
Silkyware replaces document-centric knowledge processes with AI-native workflows.
AI prepares and structures the work, your rules validate it, and experts decide what becomes organizational knowledge. Your AI assistants then consume it directly - and documents are generated when people or existing processes need them.
AI can propose. Your experts decide what becomes knowledge.
AI proposes · your domain model validates · your expert approves
Guided applications
Purpose-built applications guide a domain expert through creating something real - a standard, a procedure, a methodology, a competency profile. It begins as an interview rather than an empty form.
No form needs to exist first. Silkyware can generate and configure the guided workflow for a specific kind of knowledge from your domain model, your rules and the outcome you need - so a competency profile, a technical decision and a risk assessment each get their own way of working, all writing into the same governed source. Experts work in their domain's language; the structure underneath is Silkyware's job.
You describe what you need in your own words and the AI asks the follow-up questions, already working from the knowledge and the rules your organization has in place.
The AI generates the first full draft, then keeps working inside it - drafting a description, proposing a relation, filling in the fields it can infer. The expert adds, edits and removes.
Your domain rules are checked, and anything the draft would duplicate or change is surfaced before it can be saved.
The final step shows what enters the knowledge base and what it supersedes. Approval remains an explicit decision by a named person.
Governance by design
Silkyware separates what AI suggests from what your organization knows.
01 · Validate
Define what may exist, how concepts relate and which rules must hold. Proposed changes are validated before they can enter the governed knowledge base.
Invalid structures do not become warnings buried in a workflow. They are rejected at the boundary.
02 · Approve
Every AI-generated change begins as a proposal. Reviewers see what is being added, changed or replaced and explicitly decide whether it becomes part of the authoritative record.
Every approval remains attributable to the person who made it.
03 · Record
Knowledge evolves without erasing its past. When something changes, the previous version is superseded rather than overwritten, with the full record of what changed, when, and who approved it.
With the ability to revert when necessary.
The knowledge lifecycle
Existing knowledge can be imported. New knowledge no longer needs to start in a document.
01A · EXISTING KNOWLEDGE
Import documents, spreadsheets, registers, databases and existing systems. Silkyware structures them into governed knowledge.
01B · NEW KNOWLEDGE
Start from an expert's intent. Silkyware can generate and configure the AI-guided workflow around your domain model, existing knowledge and rules - no Word or Excel template required.
Both paths enter the same governed lifecycle
Structure, relationships and updates arrive as a proposal. AI proposes; it does not decide what becomes authoritative knowledge.
Checked against your domain model and methodology, with duplicates and conflicts surfaced.
Reviewers accept or reject individually. Nothing publishes without a decision, and history is kept.
Word, Excel, PDF, wiki pages, APIs and AI systems all read the same governed knowledge.
Works with the AI you already use
ChatGPT, Copilot, Claude and Gemini are getting very good at finding organizational knowledge and using it as context. Silkyware is not another assistant. It is the layer underneath that makes what they find worth trusting.
01 · Govern
Permissions, connectors and audit logs control how AI reaches your information. They cannot answer who says it is correct, which version is authoritative or who approved the change.
Silkyware answers those questions where knowledge is created.
02 · Author
Experts maintain structured, governed knowledge instead of maintaining files. Word, Excel, PDF and wiki pages are generated from that knowledge.
The file is a view of the knowledge, not the place it lives.
03 · Connect
Every assistant and agent in your organization reads the same governed source - current versions, provenance and permissions included.
And what an agent proposes back enters through the same expert approval gate as everything else.
AI can make Word and Excel smarter. Silkyware makes them optional.
Beyond one domain
Every organization describes its world differently. The underlying requirement is remarkably similar: information must become authoritative through a controlled process before people, software or AI can safely rely on it.
A project must always make clear which information is current, who approved it and what it replaced. Using a superseded drawing, requirement or technical solution can become a real error on site.
Procedures, specifications and work instructions must make clear which version applies, when it changed and who approved the change. Earlier versions remain traceable.
When new versions are published, the relationship to earlier codes, concepts and classifications must remain visible. It should always be possible to understand what changed and how old and new versions relate.
The vocabulary changes. The governance model does not.
KnowledgeOps
A file becomes authoritative the moment someone saves it. Nobody validated it, nobody approved it, and nobody can say what it replaced.
KnowledgeOps means knowledge becomes authoritative by decision, not by being saved.
So people, processes and AI systems rely on the same checked knowledge - and the document is its output, not its source.
Built for trust
Silkyware runs end to end in the cloud with enterprise authentication, organizational isolation and real workflows.
Not a prototype. Not a slide deck.
Every governed change carries history, attribution and approval context, creating a record designed for organizations that need to demonstrate how knowledge became authoritative.
Your organization's knowledge remains isolated and access-controlled, with permissions designed around the people and systems that should be able to use it.
Use leading commercial AI models today while retaining the freedom to change providers or run models in your own environment as your security and deployment requirements evolve.
Get in touch
Bring us an existing knowledge base — a register, methodology, classification or document set — or a knowledge-heavy process you want to rebuild. "Every month six engineers spend three days producing this specification" is exactly the right conversation.
We work closely with a small number of organizations at a time, so every conversation starts with your domain rather than our demo environment.