Capabilities
Research, prototype, and build the product your problem requires.
Engagements move through four phases. Not every project needs all four — some start at research, some arrive with a validated idea and go straight to build — but the sequence is how uncertain problems become reliable software.
Investigate
Understand the work before choosing the technology.
- Domain and workflow research
- User interviews
- Technical landscape analysis
- AI opportunity identification
- Data and integration assessment
- Feasibility studies
- Risk identification
Prototype
Test the hardest assumption before building everything.
- Interaction prototypes
- Model and agent experiments
- Retrieval systems
- Technical proof of concept
- Pilot workflow
- Evaluation plan
- User testing
Build
Turn the validated approach into reliable software.
- Product architecture
- UX and interface design
- Full-stack development
- AI integration
- Infrastructure
- Authentication
- Data systems
- Deployment
Improve
Evaluate, refine, and uncover the next question.
- Observability
- Model and product evaluation
- User feedback
- Workflow refinement
- Performance optimization
- New research questions
- Continued development
Qualification
Is DataKnife the right fit?
We would rather tell you early. Both lists are honest.
A good fit when
- The product is technically uncertain.
- The workflow is specialized.
- Existing software does not fit.
- Human interaction is as important as model performance.
- The organization needs both investigation and development.
- The system must move beyond a demo.
Probably not the best fit when
- The project is a basic marketing website.
- The goal is only to replicate an existing application.
- The client wants staff augmentation without product ownership.
- There is no willingness to test assumptions.
- The only requirement is the lowest possible implementation cost.
Not sure which phase your problem is in?
That is normal — placing the problem correctly is the first thing we do together. Describe it as it actually is.