Vibecoding made developers faster. But delivery cycles? Those didn't change.
AiSpecify is enterprise-native AI dev platform that addresses this by governing the entire software development lifecycle. It helps your many teams auto-generate specs, codify with embedded controls, test in provisioned environments, and ship audit-ready applications. From business intent to governed production.
Vibecoding stops at the IDE. AiSpecify governs the full lifecycle — requirements, specs, code, tests, deploy. See spec-driven, enterprise-native AI at work across four SDLC workflows.
Watch diverse inputs - prompts, documents, GitHub repos, AI-driven market research - auto-generate validated requirements, then comprehensive functional and non-functional specifications: user flows, user stories, data models.
Watch a regulated organization define a custom specification - a risk artifact required by compliance - that AI must always produce, populated from the data model, security review, and PII handling rules.
Watch AI compose your application from a built-in library of Lensing enterprise services, SAP APIs, and any REST or OData endpoint - then generate a live UI prototype with role-based access controls baked in, down to the component or field.
Watch quality checks surface consistency issues by severity, AI rectify them (or you do), and the build trigger only once the review is clean.
CIOs are being asked to show AI value and cut software, SIs, and headcount costs at the same time. Vibe coding tools help with the 20% of the lifecycle inside the IDE. The other 80% is where the budget actually goes.
Most AI tools improve one step in the lifecycle. AiSpecify governs all of it — turning business intent into a deterministic blueprint, then carrying that blueprint through code, test, and release with the audit trail intact.
Inputs from prompts, documents, market research, and existing repos become comprehensive functional and non-functional requirements — and a deterministic specification with your governance and regulatory guardrails built in.
The blueprint is built using enterprise-grade services for identity, security, data, eventing, and observability. Not boilerplate. Not generic scaffolding.
Auto-provisioned environments validate the build, with consistency checks running across the full spec set — surfacing contradictions and gaps before code ships.
Controlled, audit-ready release management with role-based access, environment versioning, and full traceability from prompt to production.
Inputs from prompts, documents, market research, and existing repos become comprehensive functional and non-functional requirements — and a deterministic specification with your governance and regulatory guardrails built in.
The blueprint is built using enterprise-grade services for identity, security, data, eventing, and observability. Not boilerplate. Not generic scaffolding.
Auto-provisioned environments validate the build, with consistency checks running across the full spec set — surfacing contradictions and gaps before code ships.
Controlled, audit-ready release management with role-based access, environment versioning, and full traceability from prompt to production.
“”This is far beyond code generation. It's end-to-end delivery of software - from requirements to production - leveraging AI natively as you should.
Spent 26 years at SAP as EVP of Technology. Franz was the original architect of SAP HANA.
Was VP of Product for the quality and manufacturing suite at Veeva Systems.
Former SVP of product and technology at SAP where he worked for 22 years.
Jeff was the Global Revenue Controller who took PagerDuty public.
Was J.P. Morgan’s Chief Innovation Officer for Global Banking and former Chief Design Officer for SAP.
Former Managing Director of New Business Ventures at J.P. Morgan. Led multiple functions at various startups and SAP.
Former controller with international accounting experience.
AiSpecify is an enterprise-native AI platform for spec-driven software development. It translates business intent — from prompts, documents, market research, or legacy code — into deterministic specifications, then governs the full software lifecycle through codification, testing, and deployment.
Unlike AI coding tools that focus on accelerating individual developers inside the IDE, AiSpecify governs the 80% of the software lifecycle that happens outside the IDE: requirements engineering, governance enforcement, consistency checking, role-based access controls, and audit-ready release management. The result is enterprise software that AI can generate, govern, and deploy with the controls regulated organizations require.
Spec-driven development is a software development approach where a structured specification — not the code itself — is the source of truth. Teams define what to build through a comprehensive set of functional and non-functional requirements, and AI uses that specification as a deterministic blueprint for everything that follows: build, test, and deployment. If the code and the spec disagree, the code is wrong.
Spec-driven development emerged as the enterprise alternative to "vibe coding," where developers prompt AI iteratively without structured upfront definition. Vibe coding works for prototypes but produces code that drifts from intent, lacks governance, and creates audit-trail gaps in regulated environments. Spec-driven development moves architectural, security, and compliance decisions upstream — before code is generated — so AI-generated software can be trusted in production.
Vibe coding tools — AI assistants embedded inside developer IDEs — help individual developers write code faster, typically improving productivity by 15–20%. But the IDE represents only one step in the software development lifecycle. Requirements gathering, specification writing, governance review, testing, deployment, and audit trails all happen outside the IDE and remain largely manual.
AiSpecify governs the full lifecycle. It auto-generates functional and non-functional requirements from diverse inputs, embeds organizational governance and regulatory guardrails before code is written, runs consistency checks across the full specification set, and provides audit-ready release management with full traceability from prompt to production. The difference is end-to-end governance, not faster code generation.
AiSpecify embeds governance into the specification itself, before any code is generated. Through a feature called Custom Specs, organizations encode their own guardrails — risk documentation requirements, security review templates, PII handling rules, regulatory artifacts — and AI is required to produce them as part of every build. Governance becomes part of the deterministic blueprint, not a review gate after the fact.
The platform also provides role-based access controls at the page and feature level, environment versioning for sandbox and production isolation, consistency checks that surface contradictions and gaps before code ships, and full traceability from initial prompt through code, test, and release — the audit trail compliance, security, and regulatory teams require.
