Governed Analytics

Give business teams answers without losing SQL control.

When every off-dashboard question becomes an analyst ticket, we build governed answer workflows with approved data scopes, visible SQL, business definitions, and validation before rollout.

Workflow Value

From painful repeatable work to defensible action.

Business users wait days for SQL queries

When every operational question requires a data engineer to write custom SQL, decision-making slows and data teams become a queue. We implement governed answer workflows so approved users can ask recurring questions without bypassing controls.

The problem with generic Text-to-SQL

Generic text-to-SQL tools can join the wrong tables, use the wrong business definition, or ignore permission boundaries. Our systems use approved semantic context, verified joins, visible SQL, and validation questions before teams rely on the output.

Governed SQL transparency & validation

Every plain-English question produces inspectable SQL, result tables, charts where useful, and an answer narrative. Data owners can review the generated query, business definitions, filters, and source scope before trust is expanded.

Architected for zero data movement

We deploy within your VPC. The system connects to Snowflake, BigQuery, or PostgreSQL using read-only credentials. It enforces your existing Row-Level Security (RLS) policies by injecting user identity context into every generated query.

Workflow Architecture

How the system works behind the page.

Every solution is implemented as a controlled workflow, not a loose chatbot. The system operates inside approved data and tool scopes, produces inspectable outputs, and routes judgment back to the right human owner.

Scope the job

Define the exact workflow, input sources, business rules, user roles, output format, and what the AI agent is allowed to do.

Retrieve the right context

Pull only approved documents, records, ERP context, control libraries, or playbooks before the agent drafts or acts.

Produce source-visible output

Generate findings, matrices, notes, SQL-backed answers, or queues with source references, exception reasons, and confidence signals.

Validate before expansion

Measure reviewer edits, pass/partial/fail outcomes, time saved, exception quality, and adoption before moving to adjacent workflows.

FAQ

Frequently asked questions

Does this require moving our data?

No. We connect to existing warehouses such as Snowflake, BigQuery, or Postgres using read-only credentials and approved network paths.

Can it handle complex, messy database schemas?

Yes. We implement a semantic layer that maps your complex database schema into clear business definitions, allowing the AI to generate accurate queries.

Automate one repeatable workflow.

Bring the workpaper, evidence review, diligence process, ERP answer queue, or reporting loop that consumes the most hours. We will map a practical workflow around your methodology.