'%3e%3cellipse%20cx='185.202'%20cy='292.401'%20rx='236.2'%20ry='212.4'%20transform='rotate(180%20185.202%20292.401)'%20fill='url(%23paint0_radial_6113_7068)'/%3e%3c/g%3e%3cdefs%3e%3cfilter%20id='filter0_f_6113_7068'%20x='-130.996'%20y='0.000976562'%20width='632.398'%20height='584.8'%20filterUnits='userSpaceOnUse'%20color-interpolation-filters='sRGB'%3e%3cfeFlood%20flood-opacity='0'%20result='BackgroundImageFix'/%3e%3cfeBlend%20mode='normal'%20in='SourceGraphic'%20in2='BackgroundImageFix'%20result='shape'/%3e%3cfeGaussianBlur%20stdDeviation='40'%20result='effect1_foregroundBlur_6113_7068'/%3e%3c/filter%3e%3cradialGradient%20id='paint0_radial_6113_7068'%20cx='0'%20cy='0'%20r='1'%20gradientUnits='userSpaceOnUse'%20gradientTransform='translate(-43.0144%20248.324)%20rotate(-25.0248)%20scale(462.733%20514.489)'%3e%3cstop%20stop-color='%23FF9DDA'/%3e%3cstop%20offset='0.44'%20stop-color='%23F7FF9D'%20stop-opacity='0.52'/%3e%3cstop%20offset='0.84'%20stop-color='%23FF8B7B'%20stop-opacity='0.2'/%3e%3cstop%20offset='1'%20stop-color='%23F7FF9D'%20stop-opacity='0'/%3e%3c/radialGradient%3e%3c/defs%3e%3c/svg%3e)
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. Each artifact becomes the deterministic blueprint that drives your build. This is the upstream gap vibecoding tools leave wide open.
'%20fill='url(%23paint0_radial_6187_8177)'/%3e%3cdefs%3e%3cradialGradient%20id='paint0_radial_6187_8177'%20cx='0'%20cy='0'%20r='1'%20gradientUnits='userSpaceOnUse'%20gradientTransform='translate(19.9581%20420.809)%20rotate(-25.0248)%20scale(1156.83%201286.22)'%3e%3cstop%20stop-color='%23FF9DDA'/%3e%3cstop%20offset='0.44'%20stop-color='%23F7FF9D'%20stop-opacity='0.52'/%3e%3cstop%20offset='0.84'%20stop-color='%23FF8B7B'%20stop-opacity='0.2'/%3e%3cstop%20offset='1'%20stop-color='%23F7FF9D'%20stop-opacity='0'/%3e%3c/radialGradient%3e%3c/defs%3e%3c/svg%3e)
New at Everest
AiSpecify is Enterprise-Native AI
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.
See it in Action
Governance is the moat
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.
Specs that drive the build
Guardrails AI must honor
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. Governance becomes part of the build, checked before code generation, not a review gate bolted on after.
AI composes your stack
Watch AI compose your application from a built-in library of Everest 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. Production-grade services and governance, not generic boilerplate.
Fully tested to production
Watch quality checks surface consistency issues by severity, AI rectify them (or you do), and the build trigger only once the review is clean. Out comes a fully functional application — with release management, environment provisioning, release notes, and documentation generated alongside. This is what Enterprise-Native AI delivery looks like.
THE REALITY UNDER PRESSURE
AI for the IDE isn't AI for the SDLC
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.
Spec-driven development. Four governed phases.
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.
01. SPECIFIED
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.
02. CODIFIED
The blueprint is built using enterprise-grade services for identity, security, data, eventing, and observability. Not boilerplate. Not generic scaffolding.
03. TESTED
Auto-provisioned environments validate the build, with consistency checks running across the full spec set — surfacing contradictions and gaps before code ships.
04. DEPLOYED
Controlled, audit-ready release management with role-based access, environment versioning, and full traceability from prompt to production.
Production-tested. Ready to compose.
AiSpecify ships with a library of enterprise-grade services for spec-driven AI development — identity, security, data, workflow, observability — that AI knows how to use. Plus SAP integrations and any REST or OData endpoint you wrap. The platform meets the stack you already run.
This is far beyond code generation. It's end-to-end delivery of software — from requirements to production — leveraging AI natively as you should.
Get a Live Demo
Enterprise-native AI
Get a live walk-through of AiSpecify.
90% of global GDP runs through software this team built
The architects behind SAP HANA, SAP Business Warehouse, SAP Analytics Cloud, and SAP Fiori Design started over. Everest's leadership team brings 150+ combined years of enterprise software experience from SAP, J.P. Morgan, Veeva Systems, and Stanford's d.school. They built the platforms the world's largest organizations run on.
Now they're building what comes next.
Franz Faerber
Franz leads Everest’s overall technology strategy, driving the architecture and product vision behind Everest’s AI-native ERP platform. He plays a hands-on role in shaping how core system functions like multi-book accounting, real-time automation, and AI workflows are delivered with both speed and scalability. His belief in the power of integrated, intelligent systems is central to Everest’s approach, that AI shouldn’t be bolted on, but woven directly into the fabric of ERP.
Franz brings over 30 years of enterprise software leadership to the company. As Executive Vice President of Technology at SAP, he was the original architect and development lead of SAP HANA, the industry’s most advanced in-memory database. He also served as Head of SAP HANA Development, managing large global teams across Germany, India, and China. His work laid the foundation for modern real-time enterprise platforms used by thousands of global organizations.
Sam Yen
Sam is a design and innovation leader who has spent 25 years helping large corporations reinvent for the better. He’s worked at small startups and some of the world’s largest software companies, as well as taught creativity and innovation at the Hasso Plattner Institute for Design at Stanford (the "d.school") and Stanford's Graduate School of Business.
Prior, Sam was Chief Innovation Officer for Global Banking at J.P. Morgan, responsible for digital products, platform, innovation, and product strategy. Prior, at SAP, he was the company’s first Chief Design Officer and helped lead an internal user experience revolution, which earned the company recognition as one of the world’s most design-centered organizations.
Sami Muneer
Sami brings 20+ years experience building and scaling enterprise software and hardware businesses. He’s worked at startups at various stages as well as large companies as J.P. Morgan and SAP. He is distinct in his breadth and depth: he’s led product and design, but also sales, marketing, customer success, and support. This gives him a practical, end-to-end understanding how great products are built, launched, and scaled.
As a Managing Director at J.P. Morgan, he led product and design in the New Business Ventures Group of their global corporate bank. Prior, he led several functions at startups focused on AI platforms and software, drones and robotics. Prior, at SAP, he launched and scaled new product lines in sports tech, energy and environment mgmt., mobile and more, several of which grew to $100M-$250M businesses.
Stefan Sigg
Stefan helps lead enterprise architecture decisions around Everest’s AI-native ERP platform. With over 30 years experience in the industry, he has helped design, build, launch, and commercialize large-scale software products used by the world’s largest companies. He has a particular expertise in product management, development, research, support, cloud operations, business intelligence, and AI.
He’s a former member of the executive board at Software AG and an SVP of Product and Technology at SAP. There, he was responsible for all aspects of the company’s global product portfolio. He played a crucial role in launching SAP Business Warehouse, SAP HANA, SAP Analytics Cloud, and much more.
Joachim Fitzer
Joachim oversees engineering at Everest, where he is responsible for building a secure, extensible platform that can support the speed, complexity, and compliance demands of modern SaaS businesses. He ensures Everest is engineered for resilience, adaptability, and performance at scale.
Prior, at SAP, Joachim served as Chief Development Architect for SAP Business ByDesign and SAP Data Hub, where he led architecture for large-scale ERP and data integration platforms. He’s an expert in multi-tenant SaaS infrastructure, metadata-driven design, and building configurable systems that balance complexity with usability.
Sandeep Chopra
Sandeep leads Everest’s product and go-to-market strategy, ensuring the platform delivers real business impact for finance and operations teams. He focuses on creating tools that empower users—not just developers—including Everest’s Live Sandbox™, no-code AI agents, and modular deployment model. His vision centers on transforming ERP from a rigid backend system into a dynamic driver of insight, agility, and strategy.
Before co-founding Everest, Sandeep was VP of Product at Veeva Systems, where he led the Quality & Manufacturing Applications Suite—a core pillar of the company’s life sciences offering. He previously held a product leadership role at NextLabs and started his career at Deloitte. With a background spanning ERP, SaaS product development, and customer success, Sandeep brings a rare blend of technical fluency and market insight to Everest.
FAQs about AiSpecify
What is AiSpecify?
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.
What is spec-driven development?
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.
How is AiSpecify different from vibe coding tools?
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.
How does AiSpecify handle enterprise governance and compliance?
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.
