Services
LLM training that ships real capability
Zenoware coaches your developers, product managers, and QA analysts through a six-week enablement programme. We map governance, teach prompt craft, wire grounded evaluation, and co-build a production-quality AI workflow anchored to your roadmap.
Programme architecture
We blend senior change management with hands-on engineering labs so your teams do more than hear the theory—they operationalise it inside live codebases. Every sprint closes with artefacts for leadership: guardrails, ROI snapshots, and adoption plans.
Diagnostic sprint
Week 1- LLM readiness audit across architecture, governance, and rituals
- Capability baseline workshop with product, engineering, and compliance leads
Curriculum build
Weeks 2–3- Role-specific playbooks for prompt craft, evaluation, and release automation
- Sandbox exercises sourced from your repositories and data contracts
Applied lab
Weeks 4–6- Guided build of a production-suitable copilot or workflow with guardrails
- Observability, evaluation, and rollout coaching handed to your enablement team
Inside each session
Foundations clinic
Prompt engineering drills, retrieval hygiene, model selection, and evaluation harnesses—teams leave with a reusable prompt and test suite library.
Applied build studio
Small squads ship a scoped pilot such as a support copilot or QA accelerator, instrumented with telemetry, fallback design, and privacy controls.
Leadership council
Product and exec stakeholders shape adoption guardrails, ROI scorecards, and an operating cadence so the lab graduates into a sustainable programme.
What leadership receives
- Executive-ready guardrails, policy templates, and communication packs for company-wide rollout.
- ROI dashboard starter with evaluation metrics, adoption scorecards, and backlog prioritisation.
- Launch plan for a production-quality copilot or automated workflow owned by your team.
Voices shaping the lab
The companies getting ahead are those pairing experimentation with disciplined evaluation and governance from day one.
The age of AI is here, and the age of copilots is here—every developer is now a prompt engineer.
Reliable AI systems require a culture of evaluation—automated tests, playbooks, and humans who understand the seams.