// Agent-delivered software

Building Software with AI, Not Just About AI

GVL.AI delivers production software through autonomous AI agent teams — from architecture through deployment, under human approval gates. Our first product, DealStack, is live with a paying customer.

DealStack shipped product
Live paying customer
< 90 days first commit to production

AI Agent Delivery

Purpose-built AI agent crews that plan, code, test, and deploy software autonomously — operating under structured governance, change management, and constitutional execution frameworks.

Autonomous Software Development

From presales through delivery. Proposal generation, solution architecture, code implementation, QA, and client handoff — each agent with defined role, scoped authority, and evidence-based completion criteria.

DealStack

The part of a business that decides what to charge, and whether to bid at all, is the only part that was never given software of its own. DealStack is that system: what to quote, what to charge, whether to bid, who approves. See DealStack →

We rebuild a business function
around AI.

Not AI bolted onto the way the work was always done — the function itself, rebuilt. Any function whose real work is decisions and documents can be done this way.

The one we have built and shipped is the commercial function. DealStack takes a request for quotation and returns a priced, audited, client-ready proposal. The AI reads; it never prices. A person approves the number before it reaches a client. It runs today with a paying customer.

Every piece of work is written down before an agent starts it, and nothing is accepted on an agent’s own word. This is how we run our own delivery, and it is how DealStack was built.

1. Write the goal The work is specified before anyone starts, with the test that decides whether it is done
2. Run it in a lane Each agent works in its own isolated environment, on one brief, with no reach beyond it
3. Attack the result A separate reviewer — a different vendor’s model — tries to break the result. Pass or fail, findings unsoftened
4. Record the evidence Every goal ends in a report: what was measured, what failed, what is still open
5. Ship through a gate Version check, live smoke suite, and a person who approves — in that order, every time

Built to last.
Built to scale.

Elias Gouvelis — Founder & Technical Lead

Building GVL.AI on the premise that AI agents can deliver software at a fraction of traditional cost and timeline, without sacrificing quality. The company runs on the same AI-first principles it delivers to clients — autonomous agents handle operations, infrastructure, and engineering internally, proving the model before selling it.

Ready to ship
with AI agents?

info@gouvelis.com →