AIBridge Request a demo

Enterprise data, automated

AI agents that build, run and explain your data platform.

AIBridge connects to your existing systems, on-premises or in any cloud, builds a governed data warehouse, keeps pipelines healthy, and gives every team answers in plain language, whatever your industry.

9Specialised pipeline agents
50+On-prem & cloud data platforms
17Languages for voice analytics
5AI model providers

What we deliver

One platform, from source system to boardroom answer

Replace a stack of separate ETL, migration and BI tools with a single platform run by AI agents and supervised by your people.

Automated ETL

Agents read your sources, design the warehouse model and generate the SQL to load it, with quality checks on every run.

Data integration

Pipeline migration

Bring Informatica PowerCenter and dbt projects across with full field lineage, instead of rewriting them by hand.

Migration

Conversational BI

Ask questions by typing or speaking. Get the query, a chart, and recommended actions in seconds.

Analytics

How an engagement runs

Live on your data in four steps

Connect

Securely connect your databases and file sources. Nothing is copied until you approve it.

Discover

Agents map tables, relationships and data quality, and propose a warehouse model.

Build

Pipelines are generated, reviewed by your team, and run idempotently on schedule.

Ask

Business users query the warehouse in plain language, in their own language.

Why AIBridge

Built for enterprises that cannot afford surprises

Automation speeds up the work. Governance keeps it safe. Every change an agent proposes is logged, explained and approved by a person.

About the company
  • Human approval on every change. Code changes, destructive SQL and outbound messages wait in a review queue.
  • Isolated per client. Each organisation's data lives in its own schema with strict separation.
  • Model choice by region. Run Claude, OpenAI, Gemini, Mistral or local models to meet data-residency rules.
  • Self-healing pipelines. Failed loads are diagnosed and patched, then re-run safely.
  • Fits your stack. Integration through the Model Context Protocol, so new sources are connectors, not projects.

Ready to see your data answer back?