Framing before building
Work starts by narrowing the opportunity until the next decision is obvious and the risk is named.
- Opportunity and decision framing
- Assumption register with owners
- Stop, adjust, or build recommendation
For B2B companies
Turn strategic opportunities into products that operate.
Basefy helps enterprise teams validate new business models, build digital products, make AI useful in real operations, and modernize products that can no longer support the business.
- Who we work with
- CEO, CPO, CTO, CINO, COO, transformation and business unit leaders
- How it starts
- One opportunity, one week of structured framing, one first output
- What stays after
- Product, operating documentation, and the team that can run it
Start from the problem you actually have.
Pick the closest description. The panel shows where work usually begins, what Basefy does, and what you get first.
First useful output
A framed opportunity with the riskiest assumption named and a first test designed.
Typical starting pointNo agreed definition of the product, several internal versions of the idea
Basefy approachOne week of framing with the people who own the outcome, then a validation plan
Capability involvedVenture strategy, product leadership, experience design
Relevant product or workOpportunity Brief Builder
The Innovation Lab model.
The Lab is how Basefy works with established companies. It is structured to produce a decision, not a report, and to leave a product your team can operate.
AI adoption and automation
AI is applied where it changes an operation, with governance and data readiness treated as part of the work.
- Workflow and data assessment
- Source-grounded retrieval and evaluation
- Human handover and audit trail
Product creation and modernization
New products get built to be operated. Existing products get made changeable again.
- Architecture and integration layer
- Release and operating cadence
- Handover to an internal team
Engagement paths.
Opportunity sprint
A short, structured framing engagement that ends with a decision and a first validation step.
Earliest stage
Build engagement
Product leadership, design, engineering, AI, and data working as one team to ship a product into operation.
Committed initiative
Modernization track
Assessment and staged rebuild of a product that has become difficult or expensive to change.
Existing product
Ongoing product and technology leadership
Continuing senior capability where an internal team needs product, technology, or AI leadership beside it.
Continuing need
Products relevant to company work
Interactive Lab Tool
Assess AI maturity before committing to an initiative.
The AI Maturity Test runs in the Basefy assessment app. It returns a maturity read, dimension-level findings, and next priorities.
Clients who found us
Bring us an opportunity.
Describe the opportunity in your own words. Basefy replies with a first read of the problem, not a generic capability deck.
- Reviewed by a product lead, not a sales queue
- We say no when the fit is wrong
- Nothing is shared outside Basefy without your approval
Frequently asked questions.
Do you work on a fixed price?
Framing engagements have a fixed scope and price because the scope is known. Build engagements are priced per phase once the first decision and architecture are clear. Basefy does not quote a price or delivery date from a form submission.
Can you work with our internal team?
Yes. Most company engagements are mixed teams. Handover to an internal team is treated as part of the work, including operating documentation and release process.
What happens to our data during AI work?
Data readiness, permissioning, and governance are part of the engagement rather than a later step. Access scope is agreed before any data is used.
Do you take equity instead of fees?
Participation models differ by engagement and are decided case by case. Nothing on this page implies a standing offer.
Is the AI Maturity Test the same as an audit?
No. It is a structured self assessment that produces a directional read and priorities. An audit involves reviewing systems, data, and delivery practice directly.