01 / Software
From idea to a system with real users on it.
Architecture, backend, frontend and mobile, built end to end in Java, Spring Boot, Node, Vue, React and Flutter.
- Custom platforms
- Multi-tenant SaaS
- Mobile apps
- Data architecture
AI and Software
We don’t hand youa roadmap.We hand you arunning system.
Most projects stall somewhere between the demo and production. Our senior engineers build custom software, cloud platforms and AI, take them all the way into production and stay on to run them. Real guardrails, and your data stays yours.
The pilotImpressive demo. Then nothing.
Tasks handled
001Intake
02Enrich
03Decide
04Human check
05Act & log
Stalled in pilot
> request received · routed by rule
> context gathered from your systems
> model proposes an action · confidence scored
> low confidence → sent to a named owner
> executed, written back, logged for audit
The demo is the easy part. Running it every day is the work.
What we build
Five layers. One working system.
One senior team designs, builds and operates every layer, so strategy reaches production without a handoff to people you have never met.
02 / Run
The team that builds it runs it.
Multi-cloud infrastructure as code, pipelines, observability and SLOs, carried by the engineers who wrote the code.
- Azure, AWS, GCP
- Terraform and Kubernetes
- CI/CD
- Observability and SLOs
- Incident runbooks
03 / Automation
Agents and workflows that do the work.
Rules handle the predictable work. AI is added only where judgment creates value, with a person on the hard cases.
- Workflow automation
- Multi-agent approvals
- Document processing
- Browser automation
- System integrations
04 / Private AI
Your model. Your data. Your hardware.
Open models fine-tuned on your terminology and documents, running on your own servers or private cloud. No third-party API, no data egress.
- Fine tuning
- On-premise inference
- Retrieval on your documents
- Evaluation harnesses
- Air-gapped environments
05 / Governance
Secure, audited and owned.
Security built to the standard regulated clients ask for, and a named owner for AI across the business.
- ISO 27001
- Audit readiness
- EU AI Act
- Fractional CAIO
- Staff training
Industries
Where our systems run.
Regulated, data-heavy environments where the system has to keep running.
- 01Healthcare and genomicsClinical data
- 02Public sectorNational platforms
- 03Banking and financeSecurity and compliance
- 04Enterprise operationsAutomation
How we work
From decision to production.
Three moves, the same senior engineers at every step. Your infrastructure stays yours.
012 to 6 weeks
Map
A senior architecture review of what you have, what to build and where AI actually pays off. You keep the documentation either way.
021 to 3 months
Build
Ship the first production system, as full delivery or as an embedded squad inside your team.
03Ongoing
Run
SLOs, monitoring and on-call from the team that built it. Expand only what proves its value.
Guardrails built in
Rules firstSupervised startHuman on hard casesLogged and reversible
Built where your data lives
AzureAWSGCPOn premiseOpen modelsCommercial APIsYour CRM and ERP
You own the code, infrastructure, accounts and model weights.
Map what to buildQuestions
How this works.
Can we use AI without our data leaving the company?
Yes. Open models can be fine-tuned on your documents and run inside your network or private cloud. Nothing goes to a third-party service, which is usually what unblocks work in health, finance, legal and the public sector.
Where does AI actually pay off?
Rarely where the hype is. The returns sit in repetitive work that still needs some judgment: intake and routing, document handling, research, drafting and reconciliation. We measure where hours and money go before choosing anything.
Do we need a Chief AI Officer?
You need the role, not always the hire. Someone must own the roadmap, the vendor choices, the policy and the reporting. We can hold that seat part-time until AI is big enough in your business to justify a permanent leader.
What about the EU AI Act?
We build the governance in as we go: an acceptable-use policy, records of what each system does, human oversight where it is required, and role-based AI literacy training for staff, which has been an obligation for companies using AI in the EU since February 2025.
What happens if we stop working with you?
You keep the code, the models, the documentation and the accounts. Your team is trained to run the systems, and the handover is part of the work, not an extra. No lock-in.
Start with the problem
Tell us what the work looks like today.
Describe the workflow or system that needs to exist, your data rules and what has already been tried. The first conversation is with the architect who would run the work, not an account manager.
Start a Conversation hello@verba.ventures