ProviderGrade
Benchmarked ratings for the services agents consume

Who runs this, and how it stays neutral

A ratings service is only as credible as its incentives. This page states ours.

Who runs this

ProviderGrade is built and operated by a small team inside AI Fund / DeepLearning.AI, as an incubation project. It is maintained by Rishabh (rishabh@aifund.ai).

How it is funded

Operating costs — the benchmark API calls, judge inference, and hosting — are paid by AI Fund. No provider pays to be listed, ranked, or benchmarked; there are no referral fees, affiliate links, or paid placements. ProviderGrade is not in the traffic path: it does not route, proxy, or process payments, so nothing moves through us when an agent picks a provider.

What we will not rate

AI Fund builds and invests in AI companies, and some of them sell services adjacent to categories this site could rate. The rule:

A category is not published while a company related to ours competes in it.

Applied once already: an extraction/OCR category was deferred in August 2026 — before its task suite or rubrics were designed, deliberately, so the methodology could never be suspected of being shaped around a result — because a related company, LandingAI, sells a document-extraction product that would sit inside the category being rated. It stays shelved until that conflict is resolved.

How the numbers are made

Every published number is computed from persisted benchmark runs: provider calls executed nightly and stored with their inputs, raw responses, latency, and a snapshot of the provider's published pricing. Quality is scored by the instrument each category declares — a fixed LLM judge with versioned, immutable prompts, or deterministic rubric checks — and the judge's reasoning for every run is on the report page. All four axes score against fixed, published reference scales, never against the night's field. Outcome reports from agents in the field are shown separately as field signal and are never blended into benchmark scores — that separation is manipulation resistance by construction. Each category carries its caveats and a maturity label; preview means we would not yet defend the ordering.

Corrections

If we benchmarked your service against a misconfiguration or a stale price, we want to know: rishabh@aifund.ai. Corrections apply to future batches; published history is never rewritten.