AI on the side of peopleAI for learning, skills and work

AI for learning, skills
and work.

Dovichi Labs is an AI-native product company building intelligent solutions, agentic systems and domain-specific AI for the future of learning, skills and work. Three products cover that path today, and we own the technology layer beneath them rather than renting it.

3 products liveUK · NGFounded 2024
Dovichi Labs agentic AI and domain-specific AI systems
Pipeline / Active
FocusLearning · Skills · Work
Learning SystemsSkills & AssessmentCareer IntelligenceStory-Led MediaCreator StudioOwned Infrastructure
01 / The problem we work on

The hard part is no longer learning. It is proving it.

Knowledge has never been more available, yet the path from learning a skill to being hired for it is still slow, unclear and badly evidenced. Learners cannot show what they can do. Employers cannot verify it at scale.

Every product we build works on one stage of that path. We started with the learners and employers we know first-hand, and we build for that route into the global job market.

03 / How we build

We own the layer
beneath our products.

Identity, usage accounting, private history, validated model output and secure cloud access are built once and shared. That is why a small team ships AI features quickly without loosening security or losing cost control — and it is a capability, not a separate business.

Explore the technology
Product ExperiencesLearning · Career · Roadmaps
Domain LayerSkills · Evidence · Roles
Reasoning SystemsPrompts · State · Validation
Context & Product DataStructured inputs · Grounding
Secure OperationsIdentity · Usage · Private history
Foundation ModelsClaude · Open models · AWS · GCP

Supported by

  • NVIDIA Inception Program member
  • Amazon Web Services
  • fal
  • Google for Startups
04 / How we decide

Evidence, not excitement.

Dovichi Labs is the public face of the method. The same rules that govern our roadmap tool govern our own product decisions.

Prefer the simpler system

If a workflow change, a search index or a rule solves the problem better than a model, we use that instead.

No fabricated returns

We set measurable pilot targets rather than promising outcomes we cannot evidence.

A human owns the decision

Consequential outcomes for a learner, candidate or employer keep a person accountable in the loop.

Exit criteria before scale

Every stage states what evidence would justify continuing, changing or stopping.

Try the roadmap tool the method is built into. It is free and it will tell you where AI does not help.

Enter Dovichi Labs