Ship AI features without mortgaging your margin.
AI for Internet & Technology
Software companies embedding AI face a different problem: not whether it works, but whether unit economics survive scale.
What makes this sector different
Per-request cost decides the business model
A feature that costs more per call than it earns cannot ship.
Quality regressions are silent
A model or prompt change degrades output with no error raised.
Multi-tenancy from day one
Isolation retrofitted after launch is expensive and risky.
Where it pays back
In-product copilot
Retrieval-augmented generationEmbed a grounded assistant with per-tenant cost metering.
Semantic search over customer data
Retrieval-augmented generationTenant-isolated retrieval with strict namespace separation.
Evaluation and regression harness
HybridCatch quality regressions before customers do.
Cost-optimised model routing
Tool-using agentRoute by task difficulty; reserve expensive models for work that needs them.
How the Internet & Technology assessment differs
Technology assessments lead on unit economics and isolation — the two things hardest to retrofit.
Compliance we ask about first
Data sources we expect
Questions this template pushes on
- What is the most you can spend per request and stay viable?
- How will you detect a quality regression after a model change?
- Is tenant isolation required at the vector-index level?
These are suggestions surfaced alongside the questions — never pre-filled answers. The assessment still asks you everything, because a score built on assumptions you never confirmed is not a score you could act on.
Scope an AI project for internet & technology
The Internet & Technology template sharpens the questions. Ten minutes gets you a feasibility score, an architecture and a costed plan.