Enterprise Delivery Intelligence
TurboBA creates a governed path from business intent to AI-assisted engineering, bringing project context, requirements, governance, validation and human approval into one delivery workflow.
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See how it works
AI is accelerating delivery. But it doesn’t fix the context.
Business intent
Fragmented context
Inconsistent requirements
Late governance
AI-accelerated engineering
Drift + rework
Enterprise delivery already loses information between business intent, requirements, refinement, governance and engineering. Faster execution does not automatically improve the context being executed.
Spec-driven development fixes this for developers. But who governs the spec? What if the context was governed before execution begins?
One governed path from intent to implementation.
01 , SOURCES + CONTEXT
Meeting notes, Jira, project documentation and designs.
02 , GUIDED DISCOVERY
TurboBA identifies missing context and asks structured questions.
03 , GOVERNED REQUIREMENTS
Requirements and acceptance criteria generated with traceability.
04 , VALIDATION
Outputs evaluated against delivery and governance standards.
05 , HUMAN APPROVAL
People retain judgement and accountability.
06 , BUILD PACK
Approved intent becomes controlled implementation guidance.
07 , ENGINEERING
Build Packs flow into your coding agent, with checks that must pass before a pull request opens.
TurboBA does the heavy lifting. People make the decisions.
Getting to a draft is easy. Getting to approved is harder.
GENERIC AI
Prompt
Plausible output
Review and rework
Context, governance and validation depend on what the team provides.
TURBOBA
Enterprise + project context
Citations + visible gaps
Validation
Human approval
Build-ready
Generic AI is powerful. TurboBA provides the governed delivery system around it.
Every requirement cites its rule. No rule, no guess.
TurboBA generates against hundreds of versioned delivery and governance rules. Every requirement shows the rule behind it. When no rule covers what you’re asking, TurboBA says so plainly instead of inventing an answer, so gaps surface before review, not after release.
ACCEPTANCE CRITERION
Given a protected field, its value is encrypted at rest.
[source: dg_ctrl_field_encryption_v1]
Linked to the versioned rule library
REQUEST RECEIVED
Search the rule library
No governing rule found. Flagged for human decision.
Not another document. Build-ready delivery context.
Spec-driven development, governed.
User stories
Acceptance criteria / BDD
Governance requirements
Non-functional requirements
API contracts
Data contracts
Data-quality rules
Implementation guidance
Artefacts are selected to fit the work. Not every story needs every artefact.
Build Pack
Approved intent, standards, citations and approvals.
Coding agent
Claude Code · Cursor · Copilot
API contract valid
Data contract tests pass
Pull request opened
Pre-flight checks passed. The approved Build Pack is ready for review.
Build Packs give coding agents a spec that already carries your standards, citations and approvals. Developers pull them straight into Claude Code, Cursor or Copilot. Pre-flight checks, such as API contract validation and data contract tests, must pass before a pull request opens.
Your delivery context. Connected at project level.
TurboBA projects connect to the systems containing the relevant delivery context. Context belongs to the project, not to an isolated AI conversation.
Project A
Jira
Figma
Frontend GitHub repo
Backend GitHub repo
Data GitHub repo
Project B
Jira
API GitHub repo
More integrations on the roadmap.
Built for enterprise control.
Single-tenant deployment
Your own environment and data stores, per customer.
Your models, your cloud
Available on AWS Bedrock.
Project-level roles
Driver, contributor and admin, enforced server-side.
Scoped, revocable access tokens
For every developer connection.
More automation. Not less accountability.
TurboBA supports both human-in-the-loop and increasingly automated workflows. But key decisions remain human.
TurboBA augments existing roles. Ownership and accountability remain human.
Governance decision
Automated work pauses for a human decision.
Story approval
Automated work pauses for a human decision.
Technical / code review
Automated work pauses for a human decision.
Don’t take our word for it. Measure it.
An objective enterprise pilot compares the same delivery work three ways: Manual today, Team + generic AI, and TurboBA.
Evaluation measure
Manual today
Team + generic AI
TurboBA
Time to first usable output
Additional time to approval
Human hours per approved item
Rework cycles
Governance gaps found after approval
Cost per approved item
Requirement-related downstream rework
Same work. Same measures. No assumed winner.
See how TurboBA can bring governed context, validation and human control into your AI-assisted delivery process.
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