See how everything connects.
Six enrichment layers turn your company's knowledge into an explorable graph. People, projects, and technologies automatically linked across every source.
Vector Search
Multiple retrieval signals work together so nothing is missed. Semantic search captures meaning. Contextual expansion surfaces related phrasing. Lexical matching catches exact terms. A neural relevance model then fuses and ranks everything into one precision-ordered result.
Deep meaning
Expanded recall
Exact match
precision-ranked results
Vector Search
Multiple retrieval signals work together so nothing is missed. Semantic search captures meaning. Contextual expansion surfaces related phrasing. Lexical matching catches exact terms. A neural relevance model then fuses and ranks everything into one precision-ordered result.
Deep meaning
Expanded recall
Exact match
precision-ranked results
#eng-infrastructure
alice: we should migrate to k8s
bob: +1, the current setup is hitting limits
carol: what about the CI pipeline?
dave: I looked at ArgoCD, it could work
... 847 messages
This channel discusses the team's migration from Docker Compose to Kubernetes, covering CI/CD implications, ArgoCD evaluation, and timeline estimates for Q3 rollout.
Summaries
Every source gets an auto-generated summary. As content changes, summaries update automatically. Parent folders and channels roll up their children into layered overviews that stay current as anything beneath them changes. Browse any source and instantly understand what it contains, always reflecting the latest state.
Summaries
Every source gets an auto-generated summary. As content changes, summaries update automatically. Parent folders and channels roll up their children into layered overviews that stay current as anything beneath them changes. Browse any source and instantly understand what it contains, always reflecting the latest state.
#eng-infrastructure
alice: we should migrate to k8s
bob: +1, the current setup is hitting limits
carol: what about the CI pipeline?
dave: I looked at ArgoCD, it could work
... 847 messages
This channel discusses the team's migration from Docker Compose to Kubernetes, covering CI/CD implications, ArgoCD evaluation, and timeline estimates for Q3 rollout.
Keywords
Automated keyword extraction pulls key terms from every document and normalizes variants into a shared vocabulary. Different names for the same concept collapse into one entry, so search finds results even when your teams use different terminology.
canonical term
Keywords
Automated keyword extraction pulls key terms from every document and normalizes variants into a shared vocabulary. Different names for the same concept collapse into one entry, so search finds results even when your teams use different terminology.
canonical term
“Alice is reviewing the k8s migration plan, looked at argocd for ci/cd and it seems solid. Bob thinks we can prob reuse the terraform configs from the aws setup last quarter, he wants to get it done by Q3”
Entities
Automated entity detection extracts people, organizations, technologies, and more from every document. Variants are resolved so the same concept is always the same node in the graph, letting you query structured connections across your entire knowledge base.
Entities
Automated entity detection extracts people, organizations, technologies, and more from every document. Variants are resolved so the same concept is always the same node in the graph, letting you query structured connections across your entire knowledge base.
“Alice is reviewing the k8s migration plan, looked at argocd for ci/cd and it seems solid. Bob thinks we can prob reuse the terraform configs from the aws setup last quarter, he wants to get it done by Q3”
Topics
Automatic topic clustering discovers themes like “infrastructure migration” or “customer onboarding” across all your content, without manual tagging. Topics connect documents across platforms, revealing how conversations, tickets, and docs relate to the same initiative.
Topics
Automatic topic clustering discovers themes like “infrastructure migration” or “customer onboarding” across all your content, without manual tagging. Topics connect documents across platforms, revealing how conversations, tickets, and docs relate to the same initiative.
Hierarchical Retrieval
Summaries at every level of the hierarchy are themselves searchable. Broad queries match folder-level overviews. Specific queries hit individual passages. One unified search across all levels. Zoom from an org-wide overview down to individual messages.
Hierarchical Retrieval
Summaries at every level of the hierarchy are themselves searchable. Broad queries match folder-level overviews. Specific queries hit individual passages. One unified search across all levels. Zoom from an org-wide overview down to individual messages.
Zero manual tagging.
The graph builds itself.
Every document enriched. Every connection surfaced.
Explore other features
Find out more about how teams are using Precognita
Deep Understanding
Vision models, layout detection, OCR, and audio processing — we understand content the way humans do.
Read moreAgents
Turn recurring questions into autonomous agents that monitor, analyze, and deliver insights on a schedule.
Read moreLearning
The system evolves with your organization — learning from usage patterns and surfacing what matters.
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