👋🏻 Meet WisdomAI at the Databricks Data + AI Summit |

See Agentic Intelligence in action

See Agentic Intelligence in action

👋🏻 Meet WisdomAI at the Databricks Data + AI Summit |

See Agentic Intelligence in action

See Agentic Intelligence in action

👋🏻 Meet WisdomAI at the Databricks Data + AI Summit |

See Agentic Intelligence in action

See Agentic Intelligence in action

Adaptive Context Engine

Context Engine for Agentic Analytics

WisdomAI's Adaptive Context Engine (ACE) builds, continuously learns from, and governs domain context — so agents stay accurate, trustworthy, and explainable over time.

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Adaptive Context Engine Hero Image
Adaptive Context Engine Hero Image

Why does context matter?

Agents need context to perform with accuracy and reliability

AI without context is pointless

LLMs possess vast knowledge but lack the specific enterprise context that makes insights accurate and relevant

Context is fragmented

Pulled from tools, docs, queries, and systems that don't naturally connect.

Ambiguous metric definitions

The same metric can mean different things to different people and table or column names confused by AI

Aggregating and validating context manually is expensive

Significant time and effort go into gathering and validating it manually

Context is perishable and goes stale quickly

As data and logic evolve, previously defined context falls out of sync

Coverage is incomplete and hard to maintain.

Critical business knowledge is often missing or never fully captured.

One question, four kinds of context

Every business question depends on business, semantic, governance, and operational context. ACE gives data teams the ability to manage all four automatically, so AI Analytics stays grounded in how your enterprise actually runs

Feature Image

WisdomAI's Adaptive Context Engine

ACE is built around five components — every feature lives inside one of them. Together they cover the full lifecycle of enterprise context.

Build

Govern

Adapt

Version

Publish

01. Build

Bootstrap business context from day one — no manual setup, no prior documentation needed.

Context Bootstrapping Engine

Connects to your data sources on day 1 and builds business context automatically — no manual setup or prior documentation needed.

Unstructured Context Ingestion

Turns docs, PDFs, Notion pages, Confluence wikis, Slack threads, and Jira tickets into structured, queryable context — no ETL required.

Live Connections & Auto-Sync

Auto-sync context in the background with scheduled refresh. Connects to GitHub, dbt, Snowflake, BigQuery, Databricks, Salesforce, HubSpot, and any MCP server.

Build

Govern

Adapt

Version

Publish

01. Build

Bootstrap business context from day one — no manual setup, no prior documentation needed.

Context Bootstrapping Engine

Connects to your data sources on day 1 and builds business context automatically — no manual setup or prior documentation needed.

Unstructured Context Ingestion

Turns docs, PDFs, Notion pages, Confluence wikis, Slack threads, and Jira tickets into structured, queryable context — no ETL required.

Live Connections & Auto-Sync

Auto-sync context in the background with scheduled refresh. Connects to GitHub, dbt, Snowflake, BigQuery, Databricks, Salesforce, HubSpot, and any MCP server.

Why Semantic Layer isn't enough?

WisdomAI Conversational BI enables analytics self-service and frees data teams for more strategic work

Dimension

Semantic Layer

WisdomAI's Adaptive Context Engine

Core question answered

Can this be computed?

Is this the right answer for how the business operates right now?

Business definitions

Metric formulas, joins, curated models

Formulas + business meaning, ownership, conventions, and usage patterns

Versioning & rollback

Git-based versioning (code-level)

Context-level versioning across data, definitions, and usage

Drift detection

Limited or external (data quality tools, tests)

Unified detection across schema, knowledge, and usage drift

Conflict handling

Centralized definitions (single source of truth)

Detects, surfaces, and resolves cross-source conflicts

Behavioral memory

N/A

Learns from queries, corrections, and usage patterns over time

Frequently Asked Questions

What is WisdomAI's Adaptive Context Engine (ACE)?

The Adaptive Context Engine (ACE) is WisdomAI’s intelligence layer for enterprise AI. It continuously extracts, organizes, updates, and governs business context from across your organization — including semantic layers, dashboards, query history, documentation, APIs, and operational systems — so AI systems can reason using trusted enterprise knowledge instead of raw data alone.

What is WisdomAI's Adaptive Context Engine (ACE)?

The Adaptive Context Engine (ACE) is WisdomAI’s intelligence layer for enterprise AI. It continuously extracts, organizes, updates, and governs business context from across your organization — including semantic layers, dashboards, query history, documentation, APIs, and operational systems — so AI systems can reason using trusted enterprise knowledge instead of raw data alone.

Why do AI agents need a context engine?

LLMs are powerful reasoning systems, but they do not inherently understand enterprise meaning, governance, or business nuance. Without context, AI systems often generate inconsistent metrics, hallucinated answers, or low-trust outputs. ACE acts as the grounding layer between enterprise systems and AI agents, helping improve accuracy, explainability, consistency, and trust.

Why do AI agents need a context engine?

LLMs are powerful reasoning systems, but they do not inherently understand enterprise meaning, governance, or business nuance. Without context, AI systems often generate inconsistent metrics, hallucinated answers, or low-trust outputs. ACE acts as the grounding layer between enterprise systems and AI agents, helping improve accuracy, explainability, consistency, and trust.

What sources can WisdomAI's ACE connect to?

WisdomAI's ACE is designed to ingest context from a wide range of enterprise systems, including semantic layers, BI tools, query logs, dashboards, GitHub repositories, notebooks, data catalogs, APIs, documentation systems, and operational platforms like CRM or ERP tools. It is also MCP-native, enabling integration with modern AI-ready systems as the ecosystem evolves.

What sources can WisdomAI's ACE connect to?

WisdomAI's ACE is designed to ingest context from a wide range of enterprise systems, including semantic layers, BI tools, query logs, dashboards, GitHub repositories, notebooks, data catalogs, APIs, documentation systems, and operational platforms like CRM or ERP tools. It is also MCP-native, enabling integration with modern AI-ready systems as the ecosystem evolves.

How does the ACE stay up to date?

ACE continuously learns from changes across schemas, dashboards, reviewed queries, user interactions, documentation, and operational systems. Instead of treating context as static metadata, it adapts over time by identifying stale knowledge, detecting conflicts and duplication, tracking drift, and incorporating new enterprise knowledge as it emerges.

How does the ACE stay up to date?

ACE continuously learns from changes across schemas, dashboards, reviewed queries, user interactions, documentation, and operational systems. Instead of treating context as static metadata, it adapts over time by identifying stale knowledge, detecting conflicts and duplication, tracking drift, and incorporating new enterprise knowledge as it emerges.

How do I know I can trust the answer?

Trust in enterprise AI depends heavily on context quality. ACE improves trust by grounding responses in governed enterprise knowledge, maintaining lineage and provenance, enforcing permission-aware retrieval, learning from reviewed interactions, and reducing ambiguity in how metrics and business concepts are interpreted across teams and workflows.

How do I know I can trust the answer?

Trust in enterprise AI depends heavily on context quality. ACE improves trust by grounding responses in governed enterprise knowledge, maintaining lineage and provenance, enforcing permission-aware retrieval, learning from reviewed interactions, and reducing ambiguity in how metrics and business concepts are interpreted across teams and workflows.

What governance and security controls are built in?

Wisdom enforces row-level security on structured data sources, so users only see the data they're authorized to access. Column-level controls enable conditional data masking, hiding sensitive fields like compensation, PII, or deal terms based on the user's role. Your existing access policies carry over. You don't rebuild them in Wisdom.

What governance and security controls are built in?

Wisdom enforces row-level security on structured data sources, so users only see the data they're authorized to access. Column-level controls enable conditional data masking, hiding sensitive fields like compensation, PII, or deal terms based on the user's role. Your existing access policies carry over. You don't rebuild them in Wisdom.

Can ACE power external AI agents and tools?

Yes. ACE is designed as shared context infrastructure for enterprise analytics. Context managed inside ACE can be exposed through APIs and MCP-compatible interfaces so external copilots, AI agents, IDEs, dashboards, and applications can consume trusted organizational knowledge without rebuilding context independently inside every product.

Can ACE power external AI agents and tools?

Yes. ACE is designed as shared context infrastructure for enterprise analytics. Context managed inside ACE can be exposed through APIs and MCP-compatible interfaces so external copilots, AI agents, IDEs, dashboards, and applications can consume trusted organizational knowledge without rebuilding context independently inside every product.

Ready to have your AI rooted in your enterprise's domain context?

See WisdomAI's context engine bootstrap your analytics domain and publish it as a governed context layer — in a single session, with your real data.

Get a Demo

Get a Demo