3–4 days
Target launch for a simple website.
Custom software development with integrated AI capabilities
AI in your product.
Purpose in every feature.
Build AI capabilities into the software people use: an application, a portal or a business workflow. The focus is what the product can help a user do, not how code is written.
Estimated delivery targets
Move quickly.
Keep the scope clear.
From idea to launch. Built at lightning speed.
Here is what a focused scope can look like.
1–2 weeks
A defined, straightforward software scope.
Around 1 month
A focused first release.
Estimated targets, confirmed after scoping.
Timelines depend on the agreed scope, ready content, integrations and timely feedback. For complex products, around one month means a focused first release, with the wider product roadmap scoped separately.
Possible product capabilities
Start with one
useful job for AI.
These are opportunities to assess, not a claim that every integration has already been delivered.
Information into a workflow
Explore extracting, classifying or summarising information from approved documents inside your application.
- Define accepted input types
- Review uncertain outputs
- Check against source material
Assistance with boundaries
Assess a contextual assistant that helps users find or understand permitted business information.
- Scope the knowledge sources
- Respect access permissions
- Show evidence and limitations
Useful support, not autopilot
Consider research support, suggested classifications or draft next steps within an existing workflow.
- Keep consequential actions explicit
- Allow human review and correction
- Provide a non-AI fallback
A real example, not a concept claim
Feasivo puts AI
inside the product.
Our own business feasibility product brings AI-assisted research with source links together with an editable financial model. It is real in-house product evidence, not an invented client case study.
Inside the Feasivo product →Permitted inputDefine the data and the user's task
AI capability inside the appReturn useful output with context
Review, edit and decidePeople stay responsible for the next step
Scope before implementation
Good AI features
need clear limits.
Not every task needs AI. Start by comparing the simplest workable approaches, then agree a contained pilot and what would count as useful evidence.
Provider choice, costs, permissions and testing are project-specific decisions.
- Data and privacyAgree allowed sources, sensitive-data boundaries, access control, retention and any third-party processing before connecting a provider.
- Quality and human reviewTest representative cases and failure cases. Define what users must verify, how errors are corrected and when the feature should decline or escalate.
- Usage and running costsEstimate likely volume, provider charges, latency and operating effort. Set agreed budgets and limits; do not assume AI features are free to run.
- Fallback and ownershipPlan for unavailable providers, incomplete output and manual completion. Agree monitoring, maintenance and responsibility after handover.
What should AI help
your users do?
Bring one real task and the information it relies on. We can scope the product capability before choosing the implementation.