Synaply enriches company knowledge with emergent topics and verifiable trust, safely captures the learnings that live in the shadows, and delivers the right evidence to every person and AI agent.
Search ranks sources and Personal Insights together, with trust metadata and citations filtered for the person asking.
Plugged into the tools you already use
Company sources stay canonical. Personal learnings stay attributable. Synaply connects both so every answer carries the right evidence, permissions, topics, and trust.
Synaply continuously syncs documents, messages, meetings, CRM records, and code. It resolves the real people, projects, companies, and decisions across every source before ranking the evidence.
Documents, threads, runbooks, and records remain the original evidence. Synaply discovers what they are about and routes the right ones through tenant-defined Verifier Agents.
Decisions, hard-won lessons, and critical context live in private messages, meetings, documents, and AI sessions. Those sources should stay private. The learning doesn't have to.
We call these hidden pockets of knowledge shadow silos.
Synaply ranks the best source evidence and Personal Insights together. Each result keeps its own origin, verification state, hashtags, attribution, and viewer-safe provenance.
Pilots most often stall when ownership is split across the customer's procurement, IT, and business teams.
A verified rollout guide defines one accountable owner, and a Personal Insight from M. Chen shows recent pilots moving faster when that pattern is followed.
No wiki page is generated. The next question is answered fresh from the same connected, permission-aware knowledge layer.
Admins define what knowledge matters and how it should be checked. Verifier Agents apply automated, human, or hybrid rubrics to both source documents and Personal Insights.
One search surface ranks verified and unverified sources alongside Personal Insights, then delivers the right cited context inside Claude, Codex, Cursor, and every connected agent.
Critical context often lives in private messages, meetings, documents, and AI sessions. Synaply synthesizes only what a person can access, sanitizes sensitive details, and lets them deliberately publish an attributable, source-backed learning.
Guided pilots with a named customer owner converted in 9 days versus the 21-day average.
Three recent incidents shared the same pattern: mocked tests passed while production migrations failed.
The same knowledge layer serves your people, their personal AI tools, and the autonomous agents doing real work — with the same permissions everywhere.
Semantic search ranks look-alike text. Synaply resolves the real business entity first, gathers the evidence that person is allowed to see, and only then ranks — inside that trusted set.
Ranks whatever sounds similar — blind to identity, permissions, and which Acme you actually meant.
Synaply's knowledge graph connects the facts scattered across your tools, conversations, and decisions into one structure your people and agents can query. It gives every answer the company-specific context behind what happened, who did it, and why.
Use the same hosted context layer that powers Synaply's knowledge layer. Building a demo is easy; keeping syncs, retries, permissions, freshness, and entity resolution alive is the product.
Entities resolve across tools so your agent can follow the thread from person to project to decision.
Sources keep their provenance while topics, verification, and Personal Insights make the right context reusable.
Synaply runs the connective tissue underneath, so product engineering stays focused on the customer.
We'll compare raw connector retrieval, Synaply's unified index, and answers enriched with trust and Personal Insights against your real organizational questions.
Test it on your knowledge