Defang Forge
Become AI-Native.
Maintain Engineering Sovereignty.
Forge is an engineering practice. Our engineers work inside your codebase and your cloud accounts to redesign how your team ships software, then hand it back to you. No slide decks. No multi-year program.
- Your cloud, your models
- We build with your team
- Running in production
Six things an assistant does not give you
Coding is one stage of producing software. These are the other six. They are what stands between a branch that looks right and a change anyone is willing to deploy on a Friday, and they are most of what an engagement builds.
Context
An agent that cannot see your architecture writes code that does not fit it. Someone has to decide what context it gets, and from where.
Access
Which tools, models and data an agent may reach, under whose credentials, with what left in the audit log.
Evaluation
Tests and evals that tell you a change is good before a human reads it. Without them, review becomes the bottleneck you moved work to avoid.
Isolation
Somewhere real to run a change and watch it behave, that is not production and not a laptop.
Observability
Production signal that flows back in, so the next change is informed by what the last one did.
Governance
The quality gates, the approvals, and the record of which agent changed what. This is the part that decides whether any of it survives an audit.
Putting those six in place is an engineering project, not a purchase. That is the work Forge does with you.
Start here
Find out where you actually are
The AI-Native Index scores your engineering workflow from 0 to 10 across six dimensions, then names the one that is holding the rest back. Most engineering organizations land between 2 and 4, at the Assisted and Integrated stages.
It takes a few minutes, it is free, and nobody calls you afterwards. Bring the result to a conversation with us, or do not.
- Design & architecture
- Coding
- Code review
- Testing & QA
- Deployment & delivery
- Operations & monitoring
What we do with you
Engagements are hands-on and engineering-led. We start from your code, your cloud accounts and your workflows.
Agentic workflow design
We find the workflows where agents earn their keep, redesign them around the people who already own them, and put the quality gates in before the agents, not after.
AI-native architecture
How models, agents and your existing services fit together. What each agent may touch. Where a human stays in the loop, and where one does not need to be.
Model and cloud strategy
Which workloads go to which cloud, which models they call, and what it costs to change your mind in a year. We do not assume one answer.
Cloud modernization
The unglamorous half. Deployment pipelines, environments, secrets and networking, so an agent has somewhere safe to ship to.
Production deployment
Getting it running in your cloud accounts with the monitoring, cost controls and rollback paths that make it something you can operate on a Tuesday.
Team enablement
Your engineers build it with us. When we leave, they own it, understand it, and can change it without calling us.
How an engagement runs
From assessment to sustained AI ROI
Start with clarity. Prove one production workflow. Use the evidence to choose what comes next.
Measure maturity, sovereignty, bottlenecks, and ROI opportunities.
Design the target workflow and production architecture.
Build one high-value production workflow with your team.
Deploy with governance in the cloud account you control.
Turn evidence into the next move and keep improving.
What you are left with
An engagement ends. The capability does not.
We count the work as done when software is running in production, not when a document is delivered.
One workflow in production
Not a pilot on a branch. Something running in your cloud account, with the monitoring, cost controls and rollback path that make it operable on a normal Tuesday.
A team that can change it
The engineers who will maintain it are the ones who built it with us. No handover document standing in for knowledge nobody transferred.
The decisions written down
Which model, which cloud, what each agent may touch, and why. So the next change is a decision you make rather than an excavation you fund.
Evidence for the next move
What changed, measured the same way you measured at the start, and a clear read on which bottleneck is now the one worth taking on.
None of it is locked to us. The cloud accounts are yours, the model and framework choices stay reversible, and the workflow is documented well enough that a team who has never met us could pick it up.
Forge builds it. You own it.
Where our own products are the right tool, we use them, and you get engineers who wrote them.
Where your agents work
Defang Station
A hosted machine running Claude Code or Codex against your own Anthropic and OpenAI accounts. Your agents get somewhere persistent to run that is not an engineer's laptop.
How the work reaches production
Defang Deploy
Your Compose file goes to your own AWS, GCP or Azure account. Preview environments for agent changes, and the same path to production for people and agents alike.
Where they are not, we use what is. Forge engagements run on GitHub Actions, Terraform, Kubernetes, Bedrock, Vertex AI, open-weight models and whatever else your stack already contains. A practice that can only recommend its own products is a sales team.
How we work
Independent
Your architecture should serve your business, not your vendors.
Defang is cloud and model agnostic, and Forge is too. Some workloads belong on AWS. Others belong on Azure, Google Cloud, your own hardware, or a mix. Some applications want Anthropic, some want OpenAI, some want an open-weight model you run yourself, and plenty want more than one. We help you pick for your data, your regulators and your constraints.
Collaborative
We build with your team, not around it.
You are not buying a parallel org that owns your roadmap for eighteen months. You are buying engineers who sit with yours, move your work forward, and explain what they did. The measure is whether your team can keep going after we leave.
Production-grade
A demo takes a day. Production takes the other things.
Deployment, monitoring, cost control, model evaluation, data governance, rollback, and a clear account of where humans and agents hand off to each other.
The factory should belong to you
How your team builds software is about to encode a lot of what your company knows: your architecture, your standards, your operational habits, your understanding of your customers. That capability should not sit inside one vendor's model, one agent framework or one cloud. Keeping it yours is what we mean by engineering sovereignty.
Tell us what your team is stuck on. You will talk to an engineer, not a salesperson.