Sanaf AI Solutions vs Runbear
The short answer: Runbear is a platform for building your own AI teammates in Slack, Teams or Discord: you create named agents like @Support or @SalesOps, give each a knowledge base and connected tools, and they answer and act with the permissions of the person asking. Sanaf is one AI employee you hire rather than build: it arrives knowing thirty five jobs, each with a written job description, works under approval rules per kind of action, and starts in shadow mode. If you have several teams that each want their own agent, and someone who enjoys setting them up, Runbear is a strong fit. If you want one colleague that takes a job and earns trust the way a person would, 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 Runbear’s own pages on 2026-09-02: Pricing page.
An illustration of how the conversation reads, not a transcript from a client account.
Runbear has been at this since 2023 and it shows. Agents are created from a chat, connect to a large catalog of tools, index your documents so they answer with citations, and can be triggered by a schedule, an event or a message in a channel. Per-user authentication means an agent acts with the asker’s own access, which security teams like, and the enterprise tier carries the certifications and the identity plumbing that procurement asks for.
The difference is who does the hiring. On Runbear you are the builder: you decide what each agent knows, which tools it has, and when it runs, and you maintain that over time. Sanaf comes with the jobs already written, adds rules per kind of action rather than per tool, holds its own scoped logins rather than borrowing yours, and drafts before it sends until you promote it. Both bill for the work rather than per seat.
How the two models differ
| Dimension | Sanaf AI Solutions | Runbear |
|---|---|---|
| What you get | Sanaf AI Solutions: One AI employee with a written job description for every job you hand it | Runbear: A platform to build named agents, one per team, each with its own knowledge and tools |
| Where it works | Sanaf AI Solutions: Slack, Microsoft Teams, and its own chat in the console | Runbear: Slack, Microsoft Teams, Discord, and inside some help-desk and CRM tools |
| Who sets it up | Sanaf AI Solutions: You pick a job it already knows, connect the apps, and it starts in shadow mode | Runbear: You design each agent: its knowledge base, its tools, its triggers |
| App credentials | Sanaf AI Solutions: Scoped to the job and held by Sanaf, revocable one at a time | Runbear: Per-user: the agent acts with the permissions of the person asking |
| Approvals | Sanaf AI Solutions: Per kind of action: do it, ask, or never, with conditions | Runbear: Approval gates you add for sensitive actions |
| Trial period | Sanaf AI Solutions: Shadow mode first, promoted a level at a time | Runbear: Live once the agent is in a channel |
| Compliance today | Sanaf AI Solutions: SOC 2 through the connection layer and hosting; our own audit is planned | Runbear: Their own SOC 2 report, with SSO and provisioning on the enterprise tier |
| 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 | Runbear: Credits per model call on monthly plans, not per seat, with an enterprise tier by quote |
Choose Runbear if
- You want several named agents, one per team, each with its own knowledge base.
- Per-user permissions matter to you: the agent should only see what the person asking can see.
- You need a vendor with its own audit report and identity provisioning today, not on a roadmap.
- You have someone who enjoys building and tuning agents and will own them over time.
Choose Sanaf AI Solutions if
- You want to hire, not build: the jobs are already written and it starts on the first one today.
- You want rules per kind of action, with a shadow period before it sends anything.
- You want the employee to hold its own scoped logins and work on a schedule, not only when asked.
- Nobody on the team wants to be the agent administrator.
Frequently asked
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