Turn business requirements into
specs for data coding agents
Kickstart your coding agent with the business logic, decisions, and validation criteria it needs to build an accurate data pipeline.
Trusted by leading organizations globally
From scattered business logic to an agent-ready data pipeline spec
Autopilot Spec turns data discovery into a structured business knowledge bundle for your data pipelines.
Resolve ambiguity before your coding agent starts building
Surface conflicting definitions, missing business rules, edge cases, and unresolved decisions before your coding agent turns them into transformation logic.
Model the scope, metrics, entities, and relationships
Autopilot Spec turns business artifacts into a structured business knowledge bundle covering the domain, use cases, KPIs, business entities, attributes, and relationships the data model needs to represent.
Generate a business specification for stakeholder review
Gain a business specification that captures the project scope and agreed business logic. Send it to domain owners before the build so the coding agent starts from the reality of how your organization operates.
Turn requirements into testable validation criteria
Autopilot Spec generates concrete business questions and answers that can be calculated from the finished data model. Use those answers as validation targets to test whether the generated pipeline matches the business requirements, not simply whether the SQL runs.
Package the approved requirements as Markdown for your coding agent
Package your business context and requirements in agent-readable Markdown. Your coding agent then uses the specification bundle to build staging, intermediate, and marts layers that carry business logic accurate to how your organization operates.
The full spec to start your project right
Project scope
What we're building, what's explicitly out, and what success looks like.
Reconciliation targets
Real figures and expected answers pulled from your inputs - revenue totals, customer counts, metric definitions - that the pipeline validates against at every step.
Business domains
Your industry, business model, org structure, and the terminology your team actually uses.
Use cases
The exact questions your stakeholders need to answer - everything else is built to serve these.
Processes
How your business actually operates: quote-to-cash, month-end close, order management.
KPIs
Your operational and financial metrics, with their definitions - not just their names.
Source systems
Every ERP, CRM, and platform involved, with modules, versions, and ownership.
Business entities
The core objects your business reasons about: customers, products, accounts, invoices.
Business rules
The constraints that make your data yours: intercompany exclusions, FX logic, fiscal boundaries.
Start with whatever you have,
agents figure out the rest
Frequently Asked Questions
Autopilot Spec is a spec builder for data coding agents. It turns business requirements from meetings, dashboards, systems of record, and other sources into a clear, agent-ready specification by resolving ambiguity and capturing the business logic your coding agent needs before it starts building.
Autopilot Spec can analyze unstructured business inputs such as meeting transcripts, emails, documents, dashboard screenshots, spreadsheets, and existing business materials to extract requirements, metrics, rules, and expected outcomes.
When requirements are incomplete or ambiguous, Autopilot Spec identifies missing information and asks you targeted questions to clarify business logic with your stakeholders before generating specifications.
Autopilot Spec generates structured specifications including business rules, data requirements, entities, relationships, metrics, validation criteria, and documentation needed for pipeline development.
A spec can reduce the gap between business teams and data engineers by converting complex business requirements into clear specifications that can be used to build reliable data pipelines faster.
Yes. Generated specifications can be reviewed, refined, and validated by business and technical teams before moving into data pipeline development.
Spec before you build
Turn business knowledge into an agent-ready spec before the first line of code.