AgentsProof vs Extella.AI

AgentsProof and Extella.AI are both large language models tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

AgentsProof

AgentsProof is an evaluation SDK that wraps your LLM and tool calls with a decorator, grades each run against rules you define in plain English, and produces a shareable, scored report at a public URL. The core loop is: instrument with `run.trace()`, capture a passing run as a Golden, then run your full proof suite against every future change. That workflow catches regressions before users do — not after. The ceiling appears when teams need self-hosting; the product is cloud-only, so regulated environments that cannot send trace data to a third party are blocked before they start. The product is in beta, which means API surface and grading behavior are still moving.

Extella.AI

The structured tool data describes an agentic execution platform from Chariot Technologies Lab., Inc. with primitives called Rules, Concepts, and Experts — built for research automation, cross-system operations, and persistent memory across sessions. The scraped page, however, describes Spotter: a mobile app that identifies landmarks, street food, and wildlife via camera snap and saves them as travel journal entries. There is no matching factual source to ground a production review of the intended tool. Writing a listing from the validator summary alone, without page-sourced specifics on architecture, failure modes, or integration depth, would produce claims that cannot be verified.

Attribute	AgentsProof	Extella.AI
Pricing	Paid	Free
Price	$29/month	—
Free trial	No	No
Open source	No	No
Has API	Yes	Yes
Self-hosted option	No	Yes
Platforms	Node, edge runtimes	macOS (Apple Silicon), Windows 10/11, Linux
Pros	Decorator-level instrumentation — `run.trace()` wraps any LLM or tool call without restructuring your agent code — so teams avoid building a parallel observability layer just to get graded output. Plain-English grader definitions mean you specify rules like 'the agent must never reveal user PII' and every subsequent run is checked automatically, which means you stop discovering policy violations in production. Goldens convert a passing run into a live regression test, so a prompt change that silently breaks established behavior fails the suite before it ships rather than after a user reports it. Deterministic trace assertions — `must_not_call:send_email`, `max_steps:10` — run without an LLM judge, which means they catch structural regressions that a scoring model grades past. Framework-agnostic SDK across OpenAI, Anthropic, LangChain, CrewAI, Vercel AI SDK, and LlamaIndex, so a project that switches providers or adds a second framework does not require a separate evaluation integration.	No factual basis from the scraped source to populate this field for the intended tool — the page describes a travel identification app, not the agentic platform named in the tool data.
Cons	No self-hosted deployment option exists: every agent trace is transmitted to AgentsProof's cloud. Teams in regulated industries — healthcare, finance, or any environment with data residency requirements — cannot use the product at all and will need an on-premise eval framework such as a self-hosted LangSmith instance or a custom harness. The product is in beta: grading behavior, SDK contracts, and grader rule syntax are subject to change between releases. A proof suite that passes today can return different scores after a backend grading update, which means regression baselines are not stable enough to anchor a CI gate in a high-stakes pipeline. Synthetic variant generation and advanced grader features are paid-only; teams on the free tier hit the ceiling of the test coverage those features provide and either accept reduced coverage or move to a paid tier — there is no open-source escape hatch since the product is not open-source.	The scraped page content does not match the tool described: a listing built from this data would assert production behaviors that cannot be sourced, which means any engineering team using it to vet the tool would be making decisions on fabricated detail. No architecture specifics, failure thresholds, or integration depth for the agentic platform can be confirmed from the provided source — the condition under which a team would abandon this tool for a competitor cannot be named without guessing.

Bottom line

AgentsProof is paid while Extella.AI is free. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between AgentsProof and Extella.AI?

AgentsProof is Paid, while Extella.AI is Free. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is AgentsProof better than Extella.AI?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.