AI analysts on your
existing data stack.

Accurate, contextual answers
without any BI migration.
Built for fast-moving operators.

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How Anko Works

Anko's ontology is the unified context layer.

It grounds every AI system you use in the semantics of your business

Flow diagram: data sources connect to Anko ontology, analysts run chat and workflows, decisions reach operators
Sources
Data Warehouse
Semantic Layer
Business Context
Ontology
Learn
Refine
Analysts
CPL · Leads
Revenue · LTV
ROAS · Spend
Orders · Churn
Chat
Live Q&A.
Deep insights. Agentic RCA.
Complex Visuals
for multi-dimensional data
Anywhere
Claude
ChatGPT
Gemini
(Access from any AI platform)
Workflows
Hourly Monitoring
Alert on Slack
Daily Reporting
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Ontology

Your business logic,
built in.

Anko's ontology stores the semantic knowledge of your business at the click of a button: metric calculations, attribute topology, tribal knowledge. Every answer Anko gives is grounded in this knowledge, not generic assumptions.

Why Anko

Why Anko over General-purpose AI

Capability
anko
AI + Connectors
Existing stack
Acts as a central repository for all your warehouse and tool integrations
Connectors are fragmented, each has to be individually setup and maintained.
Business logic
Ontology serves as a central maintainable layer for all users
Prompt-based context with no centralized semantic layer.
Token usage
Analysis environment highly optimized for token consumption
Unoptimized repetitive tool calls leads to high token bloat
Output depth
Ontology allows for deep reasoning across metrics, attributes, and tribal knowledge
Reasoning limited by the context provided in each session.
Workflows
Scheduled, stateful, and connected across sessions.
Manual setup with limited coordination and no access to prior workflow outputs
Best for
Recurring business analytics
General-purpose AI tasks and one-off analysis.
Why Anko

Why Anko over dashboards and notebooks?

Capability
anko
BI tools
Migration
No BI migration required.
Requires migration of existing BI, data models, notebooks
Business logic
Ontology purpose-built for agentic reasoning
Legacy system - business context scattered across dashboards, code, files, and prompts.
User experience
AI analysts that run work for operators conversationally.
BI Interfaces where users still do a large amount of analytical work.
Recurring analysis
Adaptive workflows that investigate what changed each time.
Scheduled refreshes, static notebooks, or one-off chats.
Stateful workflows
Workflows can access past runs and factor them into future outputs
Scheduled runs are isolated.
Memory
Multi layered memory that is dynamic and evolving
Context is reset and manually maintained.
Why Anko

Why Anko MCP over Data Warehouse MCP?

Capability
anko MCP
Data Warehouse MCP
What's exposed to AI
Multi-entity ontology with coding environment
Raw table schema with SQL execution only.
Query authorship
Agent invokes metrics, SQL is auto-generated
Each query regenerates complex voluminous SQL
Consistency across users
Ontology maintains definitions and memory centrally for all users
Inconsistencies in users' context lead to a silent drift
Business context
Fiscal conventions, attribute relationships, tribal knowledge available alongside metrics
Only data specific knowledge available, business context missing
Token consumption
Tools are highly optimized to show agents only what is necessary
Tool responses dump massive tables into the prompt consuming context window
Maintenance
Ontology updates once, propagates everywhere.
Keeps getting stale. Correctness depends on users' prompt.
Best for
Recurring deep business analysis
Direct SQL access for technical users.
Customer Stories

Loved by the best operators

Life has changed post-Anko. Data is now on our fingertips. What used to take hours is now available in minutes. What really sets it apart is the depth of its context. Anko understands the conventions and nuances of our business, and talking to it is effortless.

Nina Byram
Director of Performance Marketing, Paid Social at Open English

Backed by

Integrations

Additive, not disruptive.

Anko connects directly to your data warehouse. No migration, no new infrastructure. Connect in minutes.

  • SnowflakeCloud data platform
  • DatabricksCloud data platform
  • Google BigQueryCloud data platform
  • Amazon RedshiftCloud data platform
  • Azure SynapseCloud data platform
  • dbTSemantic layer
  • LookerSemantic layer
  • ThoughtSpotSemantic layer
  • Google SheetsFile
  • CSVFile
  • Google AlloyDBDatabase
  • Google Cloud SQLDatabase
  • SQL ServerDatabase
  • MySQLDatabase
  • PostgreSQLDatabase
  • SAP HANADatabase
  • TeradataDatabase
  • Amazon AthenaQuery engine
  • DremioQuery engine
  • PrestoQuery engine
  • StarburstQuery engine
  • Amazon AuroraDatabase
  • Amazon RDSDatabase
  • OracleDatabase