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Pinecone Nexus

Give agents knowledge

Stop letting your agents grind through brute-force retrieval. Nexus compiles your data into trusted knowledge, served in a declarative query — so agents get answers instead of chunks.

Faster task completion

30× faster time-to-completion. Retrieval loops collapse to single calls.

Higher accuracy

Task completion rates above 90%. Consistent, reliable results every run.

Governed provenance

Field-level citations. Agents access only what they're permitted to see.

Cost reduction

Up to 90% reduction in token consumption per task.

Nexus makes agents more accurate, faster, and cheaper

Nexus + KnowQL
Time0.00s
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$ agent --system nexus-knowql
Traditional Agents
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$ agent --system traditional-agentic-rag

A knowledge engine, not a

Nexus offloads reasoning from your LLM to the knowledge layer. Work that normally burns tokens at inference time happens once, upstream, when knowledge is compiled.

A knowledge engine compiles knowledge

  1. 1Compile knowledgeStructures and contextualizes data into task-specific artifacts before agents need it.
  2. 2Serve structured answersReturns typed outputs with field-level citations instead of ranked chunks.
  3. 3Focus model effortMoves reasoning out of inference time so frontier models can focus on completing tasks.

30x faster, up to 90% fewer tokens, and task completion above 90%.

A retrieval system finds chunks

  1. 1Find chunksSearches documents and returns ranked text, leaving reasoning to inference time.
  2. 2Repeat expensive workBurns tokens, adds latency, and increases variance on every single query.
  3. 3Spend effort on retrievalAgents spend most effort retrieving context, not completing tasks.

Task completion often lands around 50-60%, and output still needs human review.

Do the work once, not every query

Fetching, assembling, and reasoning over data is expensive in time, tool calls, and context tokens. Nexus does this work upstream when knowledge changes, then agents query pre-compiled artifacts in a single typed call.

Nexus
RAG & Brute Force
Sources
Data warehouse · CRM · Documents · Slack
Data warehouse · CRM · Documents · Slack
Build TimeOnce

Coding agent compiles

  1. assemble
  2. reason
  3. structure
Compiled artifacts
no build step
RuntimeEvery query
Q10.5K · 50ms

Retrieve

Q112K · ~4s
  • fetch
  • reason
  • fetch
  • reason
  • fetch
  • reason
  • assemble
  • structure
Work per query

Low

Compile once. Read N times.

High

Same work. Every query.

How Nexus organizes your knowledge

One source, many artifacts. Each artifact is shaped for the agent that needs it. Contexts group artifacts by team, and together they form your organization's operable knowledge.

Click the markers to inspect each layer.

Data Warehouse
Documents
Ticketing
CRM
ERP
+ more

Push/Fetch

Knowledge Engine

builds and tunes

Compilation

KnowQL Query

Knowledge

Context - Sales

Deal details
Risk summary
Renewal policy
Champion signal

Context - Finance

ARR movement
Usage health
Billing terms
Forecast delta

Context - Support

Escalation state
Incident pattern
SLA exposure
Root-cause cluster

Context - Marketing

Campaign impact
Attribution model
Pipeline source
Conversion driver

KnowQL

Before SQL, every application built its own data access layer. Agents face the same structural moment. KnowQL gives them a shared vocabulary that provides structured, precise, and grounded knowledge in a single call. These are the six primitives that allow agents to compose across heterogeneous knowledge sources.

ask

The goal, output schema, and contexts to query.

where

Deterministic predicates and access-control enforcement.

ground

Field-level citations with confidence tiers.

shape

Typed fields returned exactly as the agent specified.

confidence

Grounded assertions separated from uncertain inferences.

budget

Depth tier and latency envelope, plus a token budget.

Give agents knowledge today

Sign up for early access to Pinecone Nexus and KnowQL