Pick the right kind of AI before you pick a vendor.
Describe one use case. Get the five viable approaches scored side by side, a cost model at your volume, and a shortlist of models that actually fit, with the reasoning spelled out. Then ask the advisor anything about the result.
No account needed for your first report. Create one later to keep it and invite your team.
- 1Hybrid: rules + retrieval + LLM8.4
- 2Generative AI, closed hosted API7.9
- 3Classical ML classifier6.8
- 4Generative AI, open-weight6.1
- 5Symbolic / rules-based4.7
Illustrative. Your weights and constraints change the order.
Three steps, ten minutes
- 01
Describe the use case
A few questions about the problem, your data, volume and constraints. Still exploring? Pick ranges instead of numbers.
- 02
Get a scored comparison
Five approaches scored on nine weighted criteria, with rationale, risks and a cost model for each.
- 03
See which models fit
For the generative options, a shortlist from a maintained catalog: cheapest adequate, balanced, and frontier if it buys anything.
Five approaches, nine criteria
Cost, residency and lock-in are computed from the catalog and your inputs. The rest are scored by a model with a written rationale you can challenge. Weights are yours to change.
Symbolic / rules-based
Deterministic logic you can read and audit. Cheap, explainable, brittle at the edges.
Classical ML
Trained classifiers and regressors on your own data. Strong when labels exist.
Generative AI, closed
Hosted frontier models behind an API. Fastest to value; weigh cost, residency and lock-in.
Generative AI, open-weight
Open models you host. Data stays in your boundary; you own the infrastructure.
Hybrid
Rules and retrieval around a model. Often the pragmatic answer for production.
Start with your use case
One report free, no sign-up. Keep it by creating an account afterwards.