AI that ships to production.
Most AI initiatives stall in pilot. Ours go live. We build agents, automations, and AI-native features on top of seventeen years of real software engineering so your AI isn’t a demo, it’s infrastructure.
Anthropic
Google Gemini
Meta Llama
Mistral
Pinecone
Weaviate
LangChain
LlamaIndex
AWS Bedrock
Azure OpenAI
Vertex AI
Four shapes of AI done properly.
Every project starts with the workflow you actually want to change, not the model.
AI agents & copilots
Autonomous and assistive agents that handle real tasks inside your business qualifying leads, triaging tickets, drafting content, guiding users in-app.
- Sales & support agents
- In-app copilots
- Autonomous multi-step workflows
- Human-in-the-loop handoff
Process automation
Replace the manual steps across your operations with reliable, observable AI workflows that cut costs and errors.
- Data extraction & classification
- Document processing & summaries
- Email & CRM automations
- Backoffice workflows
RAG & knowledge systems
Give your team or customers answers grounded in your own content, with citations they can verify.
- Internal knowledge chat
- Customer-facing help agents
- Contract & policy intelligence
- Vector search & re-ranking
Custom models & fine-tunes
When off-the-shelf isn’t enough, we train. Fine-tunes, embeddings, and model pipelines that speak your product’s language.
- LLM fine-tuning
- Domain embeddings
- Evaluation & guardrails
- Privacy-preserving deployments
Where our clients put AI to work.
Sales & marketing
Lead scoring, inbound qualification, personalised outreach, content ops, attribution.
Customer support
Tier-one deflection, ticket triage, knowledge-grounded chat, sentiment & QA.
Operations
Document processing, workflow automation, exception handling, decision support.
Product & engineering
AI-native features, in-app copilots, search & recommendations, data pipelines.
Finance & legal
Contract review, invoice intelligence, compliance checks, audit trails.
People & HR
Resume screening, onboarding copilots, policy chat, internal helpdesks.
Our AI gets to “live in production”.
That’s the bar. Not “looks cool in a demo” live, observed, getting used every day.
“We’d been stuck in AI pilots for eighteen months. Kuberman got our internal agent into production in six weeks evals, tracing, fallback paths, the whole thing. It’s now part of how the ops team works.”
Engineering-first AI delivery.
We treat AI like the production system it is with evals, guardrails, observability, and a rollback plan.
Frame the problem
Workflow first. Which tasks, who owns them, what breaks today, what’s the win.
Prototype fast
Working prototype on real data within weeks. Measured, not vibes-based.
Harden for production
Evaluation sets, guardrails, observability, cost controls, human review paths.
Operate & iterate
Monitor quality, tune prompts & retrieval, retrain, expand scope.
Because AI is software.
A prompt is not a product. AI that keeps working in your business needs everything normal software needs integrations, tests, monitoring, auth, data pipelines, UI, support. We’ve been shipping those for 17 years. The AI is the new part; the engineering around it is not.
Model-agnostic
OpenAI, Anthropic, Google, open-weights picked for the job, not the hype.
Privacy & compliance
Data residency, PII handling, and audit trails from day one.
Evaluated, not guessed
Real eval sets and regression tests. You’ll know if it got better or worse.
Operated, not abandoned
We stay on after launch. Drift, cost, and quality are watched continuously.
Tell us the task. We’ll tell you if AI should do it.
Not every problem is an AI problem. We’ll give you a straight answer, a realistic plan, and a prototype you can actually judge.