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Relevance AI

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Panel rating · 6 judges · How to read the stars

Category median

Sovereignty: 1 of 4 dimensions proven

0–5 in half steps. 5 means the rubric's top anchor is met on the evidence.

by OnSearch Pty Ltd · relevanceai.com

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Relevance AI: AI-assisted analysis on whats-best.ai Relevance AI: AI-assisted analysis on whats-best.ai (dark)

Add ?theme=dark to the image address for dark backgrounds. The badge shows the category and the month of the latest evaluation, and EU-Made where that is the product’s provenance. It never shows a score.

Relevance AI at a glance

Vendor
OnSearch Pty Ltd
Headquarters
Not stated on the vendor’s pages as of 26 Oct 2026
Data hosting
Not stated on the vendor’s pages as of 26 Oct 2026
Free plan
Not stated on the vendor’s pages as of 26 Oct 2026
Panel verdict
The AI panel rates Relevance AI 3/5, the mean of 6 judges. Relevance AI, a no-code platform for building AI agent teams from the Australian company OnSearch Pty Ltd, is judged strongest on agent capabilities, which scores 8: evaluations gate every build path, human-in-the-loop approvals sit on the visual canvas, and the vendor states its own limit that vector search "always returns results, even if none are truly relevant". how scores are made
As of
Vendor pages captured 26 Oct 2026; evaluated by the panel 28 Oct 2026. all sources

Relevance AI alternatives, European ones first →

Read this page as one judge. Each weighs the same scores by what they care about.

The Automation Lead

Weighted verdict

Builds the agents that file tickets, draft offers and chase approvals across the ERP, CRM and wiki. Wants tools and actions with scoped permissions, MCP and an API, approval steps before anything is sent, run logs, and a way to test an agent before the whole company uses it.

Same scores as the panel view — this lens weights them the way this judge cares.

Scored by The Automation Lead

Panel median The Automation Lead This judge’s scores over the panel median. Each label opens its reasoning below.
Scores per criterion, in stars out of 5
Criterion Panel median The Automation Lead
Data use, training & retention 3.5 of 5 3.5 of 5
Models & processing location 3 of 5 3.5 of 5
Admin, identity & access controls 3.5 of 5 3.5 of 5
Integrations, connectors & knowledge 3.5 of 5 3.5 of 5
Agent capabilities & guardrails 4 of 5 4 of 5
European sovereignty 2 of 5 2 of 5

Data use, training & retention

How this is scored

What happens to prompts, uploaded files, connected data and outputs: whether any of it trains a model (the vendor's or a model provider's), how long it is kept and where logs live, whether zero-retention is available, and whether a data processing agreement covers it.

0 — No statement on training or retention; the privacy policy is a website policy that does not cover the product.

3 — A general statement that business data is "not used for training", with no word on retention, on the model providers behind the product or on logs.

5 — Business data excluded from training by contract, retention periods stated for chats and files, and a DPA offered to business customers.

8 — No-training commitments stated for the vendor and every model provider it routes to, retention configurable by the admin (including deletion of chat history), zero-data-retention terms with the model providers named, and abuse-monitoring retention described.

10 — Data use fully accounted for: training, retention, logging and abuse monitoring stated per model provider, customer-controlled retention and deletion with an audit trail, outputs and connected data treated as customer data in the DPA, and an independent audit (SOC 2, ISO 27001 or ISO 42001) covering the product.

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The Automation Lead

They state no training on customer data for their own models and publish a vendor table naming OpenAI and Anthropic with no training, no logging and a DPA; run logs have stated retention (30 days on free tier, until you delete otherwise) and an Enterprise data-retention control covers tool runs, agent conversations and versions in configurable day periods. It stops short of the higher bar because retention is Enterprise-only and must be enabled by their team, routing to any provider leaves providers beyond the two named unaccounted for, and the terms separately licence use of Client Data to improve the Solution. 5 6 7 9 13

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Models & processing location

How this is scored

Which models sit behind the product and who runs them, where inference and storage happen, whether the customer can pin processing to the EU, choose or exclude model providers, bring its own model or key, or run the product in its own cloud or on premises.

0 — The models behind the product and the processing location are not stated.

3 — The model family is named, but where inference runs and through which provider (the model maker, a hyperscaler, the vendor) is unstated.

5 — Models and their providers named, with an EU processing option stated for storage and at least the default model.

8 — Each available model listed with provider and inference region, EU-only processing selectable by the admin and enforced across models, model providers excludable, and bring-your-own-key or own-cloud deployment documented.

10 — Processing fully under the customer's control and documented: EU-only or on-premises inference for every feature including agents and connectors, open-weight or self-hosted models supported, data flows per feature published, and a residency commitment in the contract rather than on a marketing page.

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The Automation Lead

Model families and providers are named (Gemini, GPT, Claude, Kimi, GLM; OpenAI and Anthropic in the vendor table), storage region is chosen at signup among the US, EU (London) and Australia, they self-host OpenAI plus open-weight models like LLaMA and Fireworks in their own multi-region AWS and Azure, and routing to any provider with customer-managed keys is supported. The pages name no inference region per model and we found no public information on an EU-only inference setting that is enforced across models; single-tenant is stated to be in the works. 1 5 9 13

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Admin, identity & access controls

How this is scored

What the IT department controls: SSO and SCIM provisioning, roles and groups, which models, agents and connectors each group may use, retrieval that respects the permissions of the source system, audit logs, usage reporting, and policies such as data-loss prevention — and whether reporting on staff use is scoped and documented.

0 — No admin features documented; accounts are individual sign-ups.

3 — A team workspace with an owner and member invitations, but no SSO, no roles and no audit log.

5 — SSO, admin and member roles, user management, and an admin view of usage.

8 — SAML/OIDC SSO with SCIM provisioning, group-based permissions for models, agents and connectors, retrieval that inherits source-system permissions, exportable audit logs, and usage analytics with documented scope.

10 — Governance a regulated company can operate: fine-grained policies (DLP, content filters, prompt and output logging rules), audit logs streamed to a SIEM, per-agent ownership and approval, usage reporting that can be aggregated or pseudonymised for works-council agreements, and every admin action logged.

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The Automation Lead

SAML 2.0 and OIDC SSO via WorkOS with identity-provider group sync and automated provisioning, role-based access at organization, project and asset level plus fine-grained access for Enterprise, audit logs streamable to your own S3 bucket, OpenTelemetry event streaming, and an API for managing projects and users — that is most of what my IT side needs. But SSO is Enterprise-only, we found no public information on retrieval that inherits the permissions of the source system, and email is the identity anchor: an email change provisions a fresh account with no permissions or owned assets transferred. 3 7 9 10

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Integrations, connectors & knowledge

How this is scored

How the product reaches company knowledge and systems: connectors to file stores, wikis, mail, CRM, ticketing and ERP, how fast and how completely they sync, the API, support for open protocols such as MCP, and how the assistant cites the sources it answers from.

0 — No integrations; users paste text or upload files one at a time.

3 — File upload and one or two connectors (for example a drive), with no API and no statement on sync or citations.

5 — A connector library covering the common file stores, wikis and collaboration tools, answers citing sources, and a documented API.

8 — Connectors to file stores, wikis, mail, CRM and ticketing with incremental sync, custom connectors or MCP support, an API and webhooks for embedding assistants and agents in other tools, and source citations on every grounded answer.

10 — The product sits in the company's systems: read and write connectors with documented scopes, MCP servers and clients, contact-centre or telephony integration where relevant, a knowledge layer that can be audited and corrected, and the data, agents and configuration exportable when the customer leaves.

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The Automation Lead

MCP support, custom connectors, an API, webhooks, cron and native CRM, email and calendar triggers, plus read-and-write Sharepoint and Confluence actions with event triggers and workspace-level shared connections — this is the connective tissue I build agents on. The captured pages give different figures for the integration count (1,000+, 1,800+ and 2,000+), we found no public information on sync speed or source citations on grounded answers, and the knowledge-search docs themselves say vector search always returns results even when none are truly relevant. 1 11 12 13 14

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Agent capabilities & guardrails

How this is scored

What an agent can actually do and where it stops: multi-step tasks, tool use and actions in other systems, scheduling and triggers, human approval before consequential actions, run logs, evaluation and testing before release, and the limits the vendor states rather than hides.

0 — No agents; the product is a chat window, whatever the marketing says.

3 — Saved prompts or custom assistants with instructions and files, but no actions in other systems and no run history.

5 — Agents that call tools or APIs and run multi-step tasks, built without code, with a log of each run.

8 — Agents that act in connected systems with scoped permissions, human approval configurable per action, triggers and schedules, test and evaluation tooling before release, and documented limits and failure handling.

10 — Agents a business can put in production and account for: versioning and staged rollout, evaluation against test sets, monitoring of quality and cost per agent, handover to a human with full context, every action attributable to the agent and the person who deployed it, and the vendor's own statement of what agents must not be trusted with.

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The Automation Lead

Agents act in connected systems with human-in-the-loop approvals you drag into the flow, triggers and schedules, version control with protected draft and active versions, full agent tracing with cost visibility, agent evaluations, A/B testing, pre-deployment scenarios and live-run sampling with pass-rate charting and drift flags — the build-test-release loop I demand before company-wide rollout. We found no public information on staged rollout, per-action attribution to the deploying person, or the vendor's own statement of what agents must not be trusted with, and they state tool inputs and outputs are not logged by Relevance AI. 1 2 3 7 9 13 14

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European sovereignty

How this is scored

Who the contracting entity and the parent company are, where customer data is hosted, and who the subprocessors are — model providers above all, then hosting, search, telephony and email. Independently sourced by the sovereignty pipeline; for an AI product the model provider is a subprocessor, so a European interface over a non-European model counts as such.

0 — Non-EU vendor and contracting entity, hosting unstated, subprocessors (including model providers) unnamed.

3 — A privacy policy exists, but hosting location is unstated or non-EU and the model providers behind the product are not named as subprocessors.

5 — EU hosting stated and an EU contracting entity, but prompts reach non-EU model providers or other subprocessors without a stated safeguard or EU region.

8 — EU hosting on named infrastructure, EU contracting entity, every subprocessor listed with its location including model providers, EU inference available, and a DPA offered.

10 — Sovereign end to end and evidenced: European ownership, entity, hosting and model processing, every subprocessor European or optional, data export and deletion documented, and a security or certification statement published rather than implied.

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The Automation Lead

The contracting entity is OnSearch Pty Ltd in Australia under New South Wales law, hosting is selectable at signup among the US, EU (London) and Australia, a subprocessor list is published at their trust centre, and the privacy policy names sub-processors in the UK, EEA, US and Australia including US model providers OpenAI and Anthropic with a DPA. No European entity or ownership is documented, the region is locked once at signup, and prompts can reach non-EU providers, which keeps it in the lower band. 5 6 9

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Pricing transparency not rated — the vendor publishes no price

How this is scored

Whether a company can compute the real annual cost from public pages alone: price per seat, per agent, per conversation or per usage unit, what is included in each tier, usage limits and overage, which models, connectors or agents cost extra, minimum seats and term.

0 — No public prices at all; every customer is a sales call.

3 — A starting price or "from" figure exists, but usage limits, included models and what scales the cost are unclear.

5 — Prices per tier are public with the main inclusions, but usage limits, overage, agent runs or enterprise features (SSO, audit logs, EU processing) are unpriced or "on request".

8 — Every tier priced publicly with seat or usage units, usage limits and overage rates, add-ons listed, minimum seats and term stated.

10 — Complete price computability: annual cost derivable for a given number of seats, agents or conversations, with every usage rate, model surcharge, add-on and support tier and the cancellation and data-return terms published.

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The Automation Lead

A public pricing page exists and the terms define the fee shape — subscription fees, paid actions where any manual, automated or scheduled tool or agent execution counts as activity, and vendor credits passed through at cost — but the captured pages show no price figures per tier and we found no public information on usage limits or overage, while SSO sits behind an Enterprise sales contact. I cannot compute an annual cost from what was captured. 3 5 8 10

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European sovereignty — proven facts

1 of 4 dimensions proven

Built only from facts shown on the vendor's own pages. A dimension we could not prove is left open, not scored as zero.

Ownership Not determined — uncited Report an error
Data residency Not determined ⚠ unverified — uncited Report an error
Subprocessors US CLOUD Act reach ⚠ unverified 0/2 pts 9 Report an error

Questions about Relevance AI

Is Relevance AI European?

No. whats-best.ai classifies Relevance AI as Rest of world.

Where does Relevance AI store data?

Not stated on the vendor’s pages as of 26 Oct 2026.

Does Relevance AI have a free plan?

Not stated on the vendor’s pages as of 26 Oct 2026.

What are the best alternatives to Relevance AI?

As of 28 Oct 2026, the panel rates Langdock (4/5), Dust (3.5/5) and Unique AI (3.5/5) highest among the other 15 AI Agents & Assistants products evaluated. Ratings that look equal are rounded to half stars; the order uses the unrounded rating, then the name. The highest-rated European alternative is Langdock (EU-Made). Ratings are the AI panel’s opinion, formed from public evidence: how scores are made. The full list, with European products first: Relevance AI alternatives.

Where this could be wrong

What we left out

A claim that does not survive our checks costs us the claim, not the page. This is what was taken off this one.

Do you know more about Relevance AI? Tell us Report an error on this page

Sources (14)

The pages every claim on this page was read from — each one checked, dated, and kept verifiable.

  1. 1 Vendor homepage relevanceai.com Checked 26 Oct 2026 Details →
  2. 2 Features page (agents) relevanceai.com Checked 26 Oct 2026 Details →
  3. 3 Pricing page relevanceai.com Checked 26 Oct 2026 Details →
  4. 4 Data security policy relevanceai.com Checked 26 Oct 2026 Details →
  5. 5 Terms naming the legal entity relevanceai.com Checked 26 Oct 2026 Details →
  6. 6 Privacy policy relevanceai.com Checked 26 Oct 2026 Details →
  7. 7 Data use, training & retention — found from sitemap relevanceai.com Checked 26 Oct 2026 Details →
  8. 8 Data use, training & retention — found from sitemap relevanceai.com Checked 26 Oct 2026 Details →
  9. 9 Admin, identity & access controls — found from sitemap relevanceai.com Checked 26 Oct 2026 Details →
  10. 10 Admin, identity & access controls — found from sitemap relevanceai.com Checked 26 Oct 2026 Details →
  11. 11 Integrations, connectors & knowledge — found from sitemap relevanceai.com Checked 26 Oct 2026 Details →
  12. 12 Integrations, connectors & knowledge — found from sitemap relevanceai.com Checked 26 Oct 2026 Details →
  13. 13 Agent capabilities & guardrails — found from sitemap relevanceai.com Checked 26 Oct 2026 Details →
  14. 14 Agent capabilities & guardrails — found from sitemap relevanceai.com Checked 26 Oct 2026 Details →