Sanaf AI Solutions vs Relevance AI
The short answer: Relevance AI is a builder platform for designing your own AI agents and multi-agent workflows, strongest for sales and operations teams with someone technical to run it, billed by credits. Sanaf is one AI employee that takes on jobs for any business, each with a written job description, working in Slack, Teams and the apps you already run. If you want to architect an agent workforce yourself with defined handoffs, Relevance AI is built for that. If you want a working colleague without becoming a builder, choose Sanaf.
Last updated 2026-09-02. Competitor details describe their model, not their current plans or prices; check their site for those.
Read from Relevance AI’s own pages on 2026-09-02: Pricing page.
An illustration of how the conversation reads, not a transcript from a client account.
Relevance AI is a serious platform. You design agents with tools, knowledge, and triggers, chain them into workflows with handoffs, and run them at scale across a large integration catalog. Teams with an operations or revenue engineer get a lot out of it, and it has platform features a team that only wants the work done will never touch.
That power is also the cost: someone has to design, test, and maintain the agents. Sanaf is the hired alternative for owners who want the employee, not the workbench. The jobs are written, the approval rules are per kind of action, it drafts before it sends until you promote it, and everything it does lands in one work log.
How the two models differ
| Dimension | Sanaf AI Solutions | Relevance AI |
|---|---|---|
| What you get | Sanaf AI Solutions: One AI employee with a job description per job | Relevance AI: A platform to design, chain, and run your own agents |
| Who it is for | Sanaf AI Solutions: Teams without a technical operator | Relevance AI: Revenue and operations teams that will build and own the agents |
| Multiple jobs | Sanaf AI Solutions: One employee, as many jobs as you hand it, each with its own rules and one shared work log | Relevance AI: Design multi-agent workflows with defined handoffs yourself |
| Where it works | Sanaf AI Solutions: Slack, Microsoft Teams, and its own chat in the console | Relevance AI: App and API triggers, chat embeds, and integrations you configure |
| Approvals | Sanaf AI Solutions: Per kind of action: do it, ask, or never, with conditions; stricter when unattended | Relevance AI: Approval steps you add to a workflow |
| Trial period | Sanaf AI Solutions: Shadow mode first, promoted a level at a time | Relevance AI: Testing tools inside the builder |
| Pricing model | Sanaf AI Solutions: Free to start with $120 of credit and no card, then credits from $20 as you need them. They never expire, and you pay for the work, not per seat | Relevance AI: Credit-based plans by volume, with enterprise pricing by quote |
Choose Relevance AI if
- You have a technical operator who wants to design and own a multi-agent system.
- Your use case is high-volume revenue operations with many defined handoffs.
- You need enterprise controls and a builder with room to grow into.
Choose Sanaf AI Solutions if
- Nobody on the team wants to be the agent builder.
- The job faces customers and needs rules for what waits for a person, set once per kind of action.
- You want logins scoped to the job, per-action approvals, and a shadow week built in rather than assembled.
- You want credit in plain dollars that never expires, and to start free.
Frequently asked
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