THE CONTEXT
MOAT.
While Vector RAG finds "similar" text, GraphRAG understands relationships. This is how Alacritous achieves near-zero amnesia.
THE CONTEXT
MOAT.
Standard AI has amnesia. Alacritous builds a persistent knowledge graph from every touchpoint—Slack, email, and docs—ensuring your AI actually knows your business.
GraphRAG Enabled
Alacritous Intelligence
VECTOR RAG
IS BLIND.
Standard Retrieval-Augmented Generation relies on semantic similarity—finding documents with matching keywords. But enterprise questions require understanding hierarchy and dependencies.
Example Failure
"How will the engineering delay impact our Q3 EBITDA target?"
Vector RAG sees "engineering" and "EBITDA" as disparate chunks. It cannot traverse the relationship between labor velocity → product delivery → revenue timing → margin.
3.4X
Accuracy Multiplier
Benchmark: Multi-hop reasoning in complex domains (2026)
INSTITUTIONAL
MEMORY.
Generic LLMs have no context. Alacritous maps your firm's relationships into an immutable Knowledge Graph.
While Vector RAG relies on simple semantic similarity, Alacritous uses relationship traversal. It doesn't just find keywords; it understands how a delay in engineering impacts your Q3 marketing budget.
3.4x
Accuracy vs Vector Search
Entity Resolution
'J. Doe' in Slack → 'John Doe' in HRIS → 'JD' in email signatures. The OS resolves every fragment into a single, traversable identity.
Ontology Mapping
Your firm's unique vocabulary, hierarchy, and tribal knowledge are encoded as structured data. Amnesia is eliminated by design.
Temporal Memory
Not just what exists, but what changed, when, and why. The Knowledge Graph maintains a full historical trajectory of every decision.
Frequently Asked Questions
What is GraphRAG and how is it different from vector RAG?
Vector RAG finds documents with similar keywords. GraphRAG understands relationships between entities — people, projects, decisions, and dependencies. When you ask "How will the engineering delay impact our Q3 target?", vector RAG retrieves separate chunks. GraphRAG traverses the relationship chain: labor velocity → product delivery → revenue timing → margin impact.
What is institutional memory and why does it matter?
Institutional memory is the accumulated knowledge about how your business operates — client preferences, decision history, process knowledge, and relationship context. Most businesses lose this when employees leave. Alacritous encodes it in a knowledge graph that persists permanently, so your operations improve over time instead of resetting with every hire.
How does the knowledge graph build over time?
Every interaction — Slack messages, email threads, CRM updates, project changes — adds nodes and edges to your knowledge graph automatically. Entity resolution links fragments ("J. Doe" in Slack, "John Doe" in HRIS) into unified identities. The graph compounds in value with every interaction, creating a structural advantage that deepens over time.
Does Alacritous store my data in the knowledge graph?
The knowledge graph captures relationships and context metadata, not raw data. Your source data stays in your systems (CRM, email, project management). The graph maps connections between entities so agents can traverse context without duplicating your data. If you cancel, you keep everything.
Related Reading
Why Your Business Has Amnesia (and How a Knowledge Graph Fixes It)
AI-Generated Artifacts — Reports Powered by the Knowledge Graph
Executive briefs, process flows, and data visualizations on demand
MCP-Native Orchestration — How We Connect 60+ Tools
The universal protocol powering the knowledge graph
ENCODE YOUR
INTELLIGENCE.
Your business relationships, client preferences, and institutional knowledge are unique. The knowledge graph compounds with every interaction — the sooner you start, the wider the moat.
30 minutes. We'll show you the graph building in real-time. No commitment.