Knowledge
Knowledge Intelligence
A dynamically constructed and continuously updated knowledge layer that connects documents, conversations, decisions, systems, and expert know-how for trusted AI context.
Technology
The Kiku Platform
Kiku unites intelligent ingestion, dynamic ontology, metadata governance, validated knowledge retrieval, and model-agnostic agent orchestration within Kiku Platform. These building blocks create a secure, privacy-conscious foundation where governed enterprise knowledge compounds across every application.
Ingestion
Documentation, cases, decisions, tribal knowledge, conversations, meetings, APIs, databases, and event streams.
Intelligence core
Knowledge intelligence layer, Agentic Resolution Engine, ontology, metadata, provenance, and agent orchestration.
Experiences
Kiku Live, Kiku Customer Support, and enterprise knowledge intelligence products.
Feature index
Jump to the platform capabilities that matter most.
Each section below maps to a core platform capability. Together, they form the governed knowledge intelligence layer and agentic engine that powers every Kiku solution.
Explore Knowledge Intelligence
Metadata
Dynamic Ontology
AI-generated and continuously updated domain ontology that understands your entities, concepts, categories, relationships, and answer paths.
AI
Agentic Resolution Flow
Self-learning workflows that orchestrate multi-step guidance using real-time context and governed knowledge retrieval.
Search
Intelligent Ingestion
AI-driven ingestion from documentation, case data, product issues, APIs, databases, and customer context, normalizing and enriching content as it arrives.
Search
Validated Knowledge Retrieval
Combined semantic, keyword, ontology, metadata, provenance, and relationship-aware retrieval at scale for enterprise relevance.
AI
AI Agent Harness
A model-agnostic framework for building specialized agents and integrating them into your stack.
Metadata
Metadata Framework
Flexible metadata modeling and filtering that flows consistently across every Kiku application.
Analytics
Analytics Showcase
Governed analytics reveal search behavior, content gaps, and operational signals across the platform.
Knowledge Intelligence
A living knowledge layer, not a static knowledge base.
Kiku's knowledge intelligence layer ingests documentation, case data, product context, customer context, decisions, conversations, and support interactions, then models the relationships between them. When an AI workflow needs context, the agentic engine retrieves validated knowledge that reflects the full situation, not just the closest article match. Every validated outcome adds confidence signals and answer patterns back into the layer.
Multi-Source Knowledge Construction
Connect documentation, historical cases, decisions, recordings, customer profiles, meetings, and enterprise systems into one governed knowledge layer.
Real-Time Knowledge Retrieval
Retrieve across product, customer, owner, decision, entitlement, and prior-work relationships as the interaction unfolds.
Closed-Loop Knowledge Learning
Write resolved outcomes, human review, agent overrides, and quality signals back into the knowledge layer so future flows improve automatically.
Core concept
Documents + Conversations + Decisions + System Context
Multi-source knowledge construction
Trusted retrieval during AI workflows
Closed-loop outcome write-back
Dynamic Ontology
A domain model that keeps learning with your business.
Kiku’s Dynamic Ontology feature builds and maintains a custom enterprise domain ontology automatically using AI. It continuously learns about your entities, concepts, categories, relationships, products, decisions, owners, customers, and answer paths as new content and signals arrive.
Ontology Bootstrapping
Analyze existing content and metadata to propose an initial domain model of entities, attributes, relationships, issue types, and case patterns.
Continuous Learning & Refinement
Update the ontology as new documentation, cases, product issues, meetings, and interactions are ingested, avoiding brittle manually curated taxonomies.
Ontology-Aware Retrieval
Improve recall and precision, understand synonyms, and bridge natural language queries to structured enterprise context.
Core concept
Entities + concepts + relationships
Ontology bootstrapping
Continuous refinement from new content
Ontology-aware retrieval
Agentic Resolution Flow
Self-learning workflows for complex issues.
Agentic Resolution Flow orchestrates multi-step guidance that adapts to the user, product, policy, channel, and retrieved knowledge context, while preserving human control.
Contextual Workflow Generation
Build answer paths that depend on the request, user profile, product state, channel, and retrieved knowledge context.
Feedback and Outcome Learning
Learn from which paths resolve issues fastest and which steps create friction, continuously refining flows.
Human-in-the-Loop Control
Allow agents to override, branch, or annotate flows, capturing expert knowledge for future automation.
Core concept
Dynamic knowledge-grounded workflows
Generate paths from issue and customer context
Learn from completed outcomes
Keep agents in control of overrides
Intelligent Ingestion
Bring every source into one governed knowledge system.
Intelligent Ingestion brings content from disparate sources into Kiku Platform using AI to normalize, enrich, and prepare it for knowledge construction, governed retrieval, and guided workflows.
Multi-Source Connectors
Ingest from documentation, files, APIs, databases, case systems, product systems, recordings, meetings, chats, and customer systems with consistent pipelines.
Content Normalization & Chunking
Normalize formats, segment content into reusable knowledge units, and attach metadata.
Enrichment & Quality Signals
Add semantic tags, entities, relationships, and quality or relevance signals for smarter retrieval and analytics.
Core concept
One ingestion fabric
Web, file, API, and database connectors
Normalization and chunking
Enrichment and quality signals
Validated Knowledge Retrieval
Relationship-aware, semantic, and keyword retrieval fused for enterprise precision.
Kiku blends semantic similarity, lexical matching, ontology awareness, metadata filters, provenance, and relationship-aware retrieval so AI gets trusted enterprise context instead of a plain vector match.
Semantic + Lexical Blending
Blend vector-based semantic similarity with keyword and field-based matching, tuned to your domain.
Ontology + Relationship Ranking
Disambiguate terms, traverse related entities, boost important enterprise relationships, and filter results using ontology and metadata.
Enterprise-Scale & Secure
Scale to millions of documents while enforcing strict RBAC filtering at query time.
Core concept
Relationship + semantic + lexical fusion
Blend vector and keyword matching
Traverse enterprise relationships
Enforce RBAC at query time
AI Agent Harness
Model-agnostic agents grounded in governed knowledge.
The Kiku Agent Harness is a framework for building and orchestrating specialized AI agents on top of your governed knowledge layer, without locking you into one model vendor.
Model-Agnostic Execution
Use your preferred LLMs and AI services while Kiku handles routing and orchestration.
Knowledge-Grounded Agents
Force agents to ground reasoning and outputs in retrieved, governed knowledge context rather than hallucinating.
Composable Tools & Actions
Give agents structured tools like retrieval, updates, and workflows under strict policies and RBAC.
Core concept
Specialized grounded agents
Route across preferred model providers
Ground outputs in governed knowledge
Compose tools and actions safely
Metadata Framework
Consistent metadata across content, search, and applications.
Kiku’s Metadata Framework provides flexible, powerful metadata modeling across all applications and content types so one governance model can shape many experiences.
Schema Definition & Governance
Define metadata schemas per domain, content type, or application.
Consistent Filtering Across Apps
Apply the same metadata filters in customer service, live chat, internal KM, and analytics.
Metadata Expansion via AI
Use AI to suggest and expand metadata, improving retrieval, analytics, and routing.
Core concept
Shared enterprise metadata
Govern schemas by domain
Apply filters consistently across apps
Expand metadata with AI assistance
Governed Analytics
See platform analytics and knowledge signals in action.
This analytics walkthrough shows how Kiku surfaces governed usage signals, content performance, and operational patterns so teams can improve retrieval quality, identify flow friction, and manage the platform with confidence.
Kiku analytics walkthrough
A screen-share tour of the active analytics experience, highlighting how the platform exposes measurable intelligence for search, content health, and operational improvement.
Proof session
Show me Kiku
against my real scenarios.
No slides. No stock examples. We tailor the proof session to your environment, your ticket types, and the outcomes your team needs to prove.
No commitment · Response within 4 hours · Proof session around your environment