Platform

A curated implementation of your data.

Meroo isn't a tool you wire up yourself. It's a curated implementation our team builds and runs for you, on a purpose-built engine. Here is the disciplined method behind it.

The method

Five phases, one curated implementation.

This is the method behind Talk to Your Database: the curation, guardrails and delivery discipline in one build. Here's how we build and run it.

01

Discover

Scope and de-risk before a line is built.

A fixed-scope sprint that gets precise about what your teams need and what your data can actually support, so the build carries no surprises.

Data estate review

The databases, scale and complexity in scope, and the state they're really in.

Use-case mapping

The questions each team needs answered, prioritised by business value.

Access, tenancy & risk

Where sensitive data, multi-tenant boundaries and compliance constraints sit.

Honest feasibility read

Where answers will be reliable, and where they won't. Set before you commit.

OutcomeA readiness plan and fixed-scope proposal, credited to the build.
02

Curate

Your business, encoded so the system can't guess.

The core of the engagement: teaching the system how your organisation actually defines things, so answers are correct and defensible.

Business vocabulary

Your terms and metrics, so 'active customer' or 'revenue' means what your company means.

Domain scoping

Your data organised into the business areas questions fall into, so reasoning stays narrow and correct.

Calculation logic

How your key numbers are really computed, not the model's assumptions.

Edge cases & data realities

The exceptions, legacy quirks and conventions that break generic tools.

Validated with your experts

Checked against how the people who know your data answer the same questions.

OutcomeAnswers that match your business, defensible to the people who know it best.
03

Guardrail

Safety in infrastructure, not a prompt.

The controls that let you trust an AI with database access, enforced below the model and verified independently of it.

Read-only access

A dedicated read-only role. The system can never write, update or delete.

Tenant & row-level isolation

Every answer scoped to the caller. Cross-customer leakage blocked in code.

Query validation

Every query checked before it runs. Unsafe or out-of-scope requests are refused, not attempted.

Scope you control

You decide which domains, tables and questions are in or out.

Full audit trail

Every question, query and result logged, with user and timestamp.

OutcomeControls hold regardless of model behavior, enforced in infrastructure, independent of the AI.
04

Deploy

Into your environment, behind your controls.

Delivered where your data already lives, integrated with your identity and access controls, in weeks.

Deployment model

On-prem, your own cloud VPC, or ours. Your data never has to leave your environment.

Identity & access

SSO/SAML and role-based access. An answer never exceeds what a person could already see.

Integration

Use our chat interface, or embed answers via API into your own product and workflows.

Phased rollout

Introduced team by team, with training and documentation.

OutcomeLive and governed within weeks of kickoff. Security review and procurement run in parallel, on your timeline.
05

Manage

Kept accurate as your business evolves.

An ongoing managed service that keeps accuracy high and coverage growing long after go-live.

Accuracy monitoring

Measured against an evaluation set, so regressions are caught before users find them.

New use-cases

Expand what teams can ask as the business grows.

Schema-change upkeep

Curation kept in step as your data model changes.

Performance & cost

Kept efficient and predictable.

OutcomeA named team keeping it trusted. Not a handoff to a ticket queue.
Why this beats “connect an LLM to your DB”

Scoping and curation are the difference.

Point a generic model at a real business database and it invents tables, guesses joins and miscalculates your metrics. On Spider 2.0, the enterprise text-to-SQL benchmark, leading models answer only about one in five questions correctly on real production schemas.

Meroo scopes every question to your curated data, reasons in your business language, and validates the result before it runs. That's what turns a demo into something you trust in production.

We validate accuracy against your own test queries during implementation, not a canned demo, so the 90%+ bar is measured on your data before you go live, not assumed from a published benchmark.

Regional health system
Works with your stack

All major databases. Always your cloud.

If our engine can generate SQL for it, we can curate it, including PostgreSQL, MySQL, SQL Server, Oracle, Snowflake, BigQuery and Redshift.

PostgreSQLMySQLSQL ServerOracleSnowflakeBigQueryRedshiftand more

Deploy anywhere

Run on-premises or in your own cloud VPC. The assistant connects with a dedicated read-only role.

Your LLM, or ours

Bring an LLM deployment you already have approved, and we configure Meroo to use it instead of ours, so there's no new AI vendor to review.

Roles, and SSO if you need it

Role-based access is built in. SAML/SSO with your identity provider is configured during implementation for teams that require it.

Embeddable

Use our chat UI, or call the API and embed accurate data answers inside your own product.

See it answer questions from your own data.

A 30-minute call. We'll show a live demo and, if it's a fit, scope a Discovery engagement.