ContextCapture
ContextCapture
Raw organizational knowledge enters here.
Ingest documents (PDF, DOCX, Markdown), videos, and audio. Source parsing, chunking, and metadata tagging feed LatticeCore data structures.
Explore ContextCapture → The Enterprise Context Layer for Agentic AI
Make AI understand how your company actually works.
Context Lattice turns documents, systems, employee knowledge, workflow friction, and operational history into a living, governed context layer that AI assistants and agents can safely use across build, execution, and operations.
Ground knowledge. Capture intent. Govern agents. Improve with every completed workflow.
Your AI does not know your company.
Even the best models struggle inside real organizations. They do not automatically know which system is trusted, which document is stale, how different roles describe the same workflow, what internal terms mean, which exceptions matter, or what decisions shaped the current process.
Your knowledge exists. It is just fragmented.
- Documents explain official process.
- Systems hold operational status.
- Teams speak in role-specific language.
- Experts remember the exceptions.
- Chats hold the real decisions and workarounds.
- Tickets and boards show intent and execution history.
- Training materials explain the ideal path — not the real one.
The problem is not that companies lack knowledge.
The problem is that AI lacks the interpretation layer needed to use it safely.
The Context Layer
Context Lattice turns scattered knowledge into AI-ready organizational understanding.
Context Lattice captures, connects, curates, packages, and activates the context that makes AI useful inside a specific company. It brings together:
Trusted source documents
Role-aware questions
Workflow scenarios
System relationships
Source-of-truth rules
Decisions and exceptions
Intent records
Agent work packets
Evaluation examples
Feedback and memory writeback
The Platform
One context layer. Seven powerful products.
Each product serves a distinct role in the context supply chain — from ingestion to orchestration.
ContextBuilder
ContextBuilder
Crowdsourced organizational intelligence.
Employee-submitted role questions, workflow friction points, internal language, edge cases, and demand signals. Community Q&A with maturity state progression from draft to verified.
Explore ContextBuilder →ContextCurator
ContextCurator
Connect and structure Capture and Builder outputs.
Kanban-style context management links ContextCapture and ContextBuilder outputs into organized, governed context objects with readiness scoring and agent work packet generation.
Explore ContextCurator →LatticeExplorer
LatticeExplorer
The structured human interface to context objects.
Explorer and Collections hierarchy for interactive browsing and querying of context atoms. Source-grounded answers, artifact generation, and context packs for export.
Explore LatticeExplorer →LatticeCore
LatticeCore
The deterministic storage backbone.
P1 CanonStore (exact-match quads for facts), P2 LatticeMem (session/role-aware memory), P3 Drop Corpus (semantic fallback). OTel-correlated trace IDs on every retrieval.
Explore LatticeCore →LatticeEngine
LatticeEngine
The execution layer for AI agents.
Context retrieval API, permission-aware context assembly, agent work packet delivery, P1 to P2 to P3 tier routing, memory writeback from verified agent outcomes, and evaluation harness.
Explore LatticeEngine →LatticeOperator
LatticeOperator
Orchestrate agents. Observe everything.
Recommend and set up agentic orchestration architectures that utilize your context. Observe the functions and activities of all CL products from a single pane.
Explore LatticeOperator → How It Works
From scattered signals to operational AI context.
Seven stages turn raw company knowledge into governed, AI-ready context — and feed every completed workflow back into the lattice.
1
Capture
Documents, system references, employee questions, friction, decisions, tickets, signals.
2
Curate
Deduplicate, source-link, permission, score, and transform input into context atoms.
3
Connect
Link roles, workflows, systems, documents, teams, decisions, and agent capabilities.
4
Compile
Assemble role playbooks, context packs, agent instructions, and evaluation datasets.
5
Activate
Route the right context into AI assistants, coding agents, copilots, and workflows.
6
Observe
Track usage, feedback, outcomes, drift, trust, citations, readiness, and gaps.
7
Improve
Feed completed work and human corrections back so every future interaction gets better.
Context Supply Chain — End to End
Sources
↓
ContextCapture + ContextBuilder
Processed chunks
↓
ContextCurator
Curated context atoms
↓
Verification workflow
Verified facts (P1 CanonStore)
↓
LatticeCore
Context packs
↓
LatticeExplorer
Agent work packets
↓
LatticeEngine
Agent or human-agent execution
↓
Memory writeback
Memory candidates
↓
Human review
Better context next time
Use Cases
Built for the moments where generic AI breaks down.
AI Assistant Readiness
Prepare assistants before you deploy them
Ground responses in trusted sources, role-aware questions, workflow scenarios, context packs, and evaluation examples before launch.
Explore this use case →Agentic Software Development
Give coding agents the context they need to act
Turn architecture docs, product intent, acceptance criteria, constraints, and prior decisions into agent-ready work packets.
Explore this use case →Operational Source-of-Truth
Answer: what is true right now?
Resolve which system to trust, who owns the next step, what changed, and what the current process actually is.
Explore this use case →Onboarding Intelligence
Up to speed in days, not months
Deliver role-specific answers grounded in current documents, training materials, workflows, and curated internal knowledge.
Explore this use case →Cross-Role Translation
Unify the language of your organization
Detect when different teams are asking the same underlying question and consolidate them into shared, reusable context.
Explore this use case →Governance & Auditability
Trace every answer and action to its source
Link responses and agent decisions back to context atoms, intent records, work packets, decisions, and human approvals.
Explore this use case → Built For
Designed for the people building, governing, and using enterprise AI.
Executives
Increase AI ROI by turning company knowledge into a reusable strategic asset that compounds over time.
Join the Founding Network →AI & Platform Teams
Stop rebuilding prompts, RAG indexes, and eval sets. Create reusable context atoms and governance patterns.
View Architecture →Engineering Teams
Give coding agents structured intent, source-grounded context, constraints, and memory from prior work.
Organize Context for Agents →Operations Teams
Resolve source-of-truth ambiguity, document exceptions, and support status-aware AI copilots.
Join the Founding Network →Employees
Shape AI around the questions, language, and workflows that matter in your daily work.
Explore ContextBuilder → What Makes It Different
Not another chatbot. Not another knowledge base.
Context Lattice treats context as a living, governed product. It does not just retrieve knowledge — it interprets, governs, packages, activates, and improves it.
| Traditional Tool | Limitation | Context Lattice Difference |
|---|---|---|
| Enterprise search | Finds documents | Connects documents to roles, workflows, systems, and source-of-truth rules |
| Chat with docs | Answers from files | Builds reusable context atoms, packs, evaluations, and memory loops |
| Knowledge base | Stores information | Turns knowledge into AI-ready operational context |
| Project management | Tracks tasks | Preserves intent, constraints, decisions, and agent execution history |
| Agent platform | Runs agents | Supplies governed, company-aware context before agents act |
| RAG pipeline | Retrieves chunks | Adds curation, provenance, permissions, maturity, and feedback loops |
The Compounding Advantage
Every completed workflow makes the next one smarter.
Most AI systems consume context but do not improve the organization's memory. Context Lattice closes the loop. Completed work creates memory candidates. Human review promotes useful learnings. Approved context becomes available for future assistants, agents, onboarding, artifacts, and workflows.
The context layer compounds over time.
The Durable Moat
The company-specific context graph — role language, workflow rules, source hierarchies, decision
history, trusted answers, employee demand signals, evaluation examples, operational feedback
loops, agent execution history, and reusable context packs. The longer Context Lattice runs,
the more valuable and harder to replicate it becomes.
Governance & Trust
Context that AI can use safely.
Context Lattice is designed for trust-sensitive enterprise environments where answers and actions must be traceable.
AI should not guess how your company works. It should rely on governed context with clear provenance, boundaries, and review.
Source-grounded answers
Citation-aware outputs
Context maturity states
Human curation workflows
Permission-aware retrieval
Source-of-truth precedence
Readiness scoring
Risk classification
Agent work boundaries
Evaluation datasets
Audit trails
Memory approval workflows
Outcomes
What better context unlocks.
More Accurate AI Answers
Ground responses in trusted sources, role context, and source-of-truth rules. Fewer hallucinations. Fewer corrections. More trust.
Safer Agent Execution
Give agents bounded, versioned, permission-aware context before they act. Constraints live in the work packet, not the prompt.
Faster AI Deployment
Reuse context packs, evaluation sets, and role playbooks across use cases. Stop rebuilding from scratch every time.
Stronger Employee Adoption
Let employees shape AI around the questions and workflows they actually have. ContextBuilder makes every contribution visible.
Better Organizational Memory
Convert completed work, corrections, and decisions into future-ready context. Every interaction makes the next one smarter.
Targets and design partner pilot metrics. Real production numbers published as Context Lattice deploys with design partner organizations.