A new product starts with identity, usage accounting, history and validated model access already solved.
Technology / The owned layerBuilt once.
Built once.
Shared across products.
Our products sit on connected layers of domain knowledge, reasoning, validated context, evaluation and secure infrastructure. We own that layer rather than renting it, which is what lets a small team ship production AI safely.
See it working in LabsOutput schema validation and human review points are defaults in the layer, not per-product decisions.
Usage accounting and model routing are visible and controlled from day one, so cost never becomes a surprise.
Learning & Assessment Systems
Our products share a model of how a skill is taught, practised, evidenced and matched to a role. This domain layer is the part a general-purpose model cannot supply, and it is where a decade of EdTech work compounds.
- Skill and role models
- Evidence and assessment structures
- Learner and candidate state
- Progression logic
Reasoning Systems
We combine prompts, application state, validation and guided workflows so model outputs are consistent enough to build a product on and reviewable enough to trust with a person’s learning or hiring outcome.
- Prompt systems
- State and workflow design
- Output schema validation
- Human review points
Context & Product Data
We structure product inputs, validated context and application state to ground prompts in the actual problem. The creator studio is the route to a distinctive African and diaspora learning content asset over time.
- Structured product inputs
- Validated context and state
- Prompt grounding
- Learning content foundations
Product Infrastructure
Identity, usage accounting, private per-user history and controlled cloud model access are built once and reused across products. Owning this layer is why a small team can ship AI features quickly without loosening security or losing cost control.
- Identity and access
- Usage accounting and controls
- Private product history
- Keyless cloud model access
Evaluation & Staged Validation
Dovichi Labs is where we release work in stages behind server, input, schema and output validation, with constrained outputs and defined exit criteria. Nothing scales until the previous stage produced evidence.
- Staged release
- Input and schema validation
- Constrained outputs
- Defined exit criteria
Product Studio
The shared layers above let us take a concept to a working product without rebuilding foundations each time. DoviLearn is the proof that the route runs all the way to an operating company.
- Concept to working product
- Shared technology foundations
- Staged commercial validation
- Operating company pathways
Product architecture
A model is the smallest part of a working product.
01Experience layer
Learning, career and roadmap product surfaces
02Domain layer
Skills, evidence, roles and progression logic
03Reasoning layer
Prompts, state, schema validation and guided workflows
04Operations layer
Identity, usage accounting, private history and cloud access