Teammates.ai deploys named AI workers — Raya for customer service, Adam for sales, Sara for interviews — that resolve tickets, run calls and screen candidates across voice, chat, email and WhatsApp in 50+ languages, with deep Arabic dialect coverage and native CRM write access.
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Teammates.ai is an autonomous AI agent platform that packages customer service, sales and recruiting as named digital workers rather than as another chat window bolted onto your website. Instead of asking you to build flows in a bot editor, it asks you to think in terms of hiring: you pick a function, you onboard a teammate to your systems and knowledge, and that teammate then owns the end-to-end loop for that function — reading context, deciding what to do, taking the action in your CRM or helpdesk, and escalating only what genuinely needs a person.
The platform ships three named AI employees: Raya handles customer service, Adam runs sales and lead generation, and Sara conducts candidate interviews. That naming is not just branding. Each one has a distinct channel mix, a distinct set of integrations, and — importantly for budgeting — a distinct billing rate, because the unit of work differs sharply between resolving a ticket, holding a thirty-minute sales call, and running a structured interview.
The company behind it is UAE-based and was founded in 2023 as Uktob.ai by Emad Ayyad and Kareem Ayyad, rebranding to Teammates.ai in January 2025 alongside a funding round backed by Hustle Fund, Access Bridge Ventures, Oraseya Capital and Beyond Capital. That heritage matters when you evaluate the product, because it explains the platform's sharpest differentiator: coverage spans more than 50 languages, and the depth of Arabic dialect support is the platform's clearest regional differentiator rather than a generic localisation checkbox. For teams serving Gulf, Levantine, Egyptian or North African customers, that distinction is the difference between an agent that technically speaks Arabic and one that sounds like it belongs in the market.
Positioned against the wider agent landscape, Teammates.ai sits between horizontal agent-builder frameworks that hand you primitives and expect you to assemble a worker, and single-channel chatbots that answer FAQs but cannot act. Its bet is on pre-built, opinionated job roles with voice as a first-class channel.
Dedicated native mobile or desktop applications are not advertised as part of the offering; the supported surfaces are the web dashboard plus the customer-facing channels listed above (To be verified).
Pricing is public and credit-based rather than purely per-seat: a free tier at $0 per month with 10 monthly credits, Pro at $25 per month with 50 credits, Business at $50 per month with 100 credits, Scale at $100 per month with 200 credits, and a custom-quoted Enterprise tier. All paid tiers advertise access to all three AI teammates and 24/7 autonomous operation, with seat counts stepping up from a single user on the free plan to unlimited on Enterprise.
You can start free with 10 credits and no credit card, which is enough to run a handful of interviews or roughly a hundred support replies before you commit to anything. The critical detail for forecasting is that credits are consumed according to the work actually performed, and the rate differs by teammate: Sara costs 10 credits per interview, Raya costs 1 credit per 10 responses, and Adam costs 10 credits per 30-minute call. That asymmetry means a support-heavy deployment and an interview-heavy deployment with identical headline volumes can differ enormously in monthly cost, so model your own mix rather than reading the tier prices alone. Premium capabilities such as custom AI personas and regional Arabic dialect tuning are positioned as Enterprise inclusions, alongside a dedicated customer success manager, the sandbox environment and quarterly business reviews. Exact entitlements and current prices should always be confirmed on the official pricing page and during signup.
Yes. There is a free tier priced at $0 per month that includes 10 monthly credits and requires no credit card, supporting a single team member. It is intended for evaluation rather than production volume.
It is primarily usage-based through credits, with tiers determining how many credits and seats you get. Because Sara consumes 10 credits per interview, Raya 1 credit per 10 responses, and Adam 10 credits per 30-minute call, your effective cost depends heavily on which teammate you use most.
More than 50 languages are supported, and Arabic dialect coverage is the platform's headline differentiator, with all dialects claimed rather than Modern Standard Arabic alone. Regional dialect tuning is positioned as an Enterprise-tier capability, so validate quality for your specific market during a trial.
They take actions. The agents update deal stages and log activity in CRMs such as HubSpot, Salesforce and Pipedrive, and read context, act and update ticket status in Zendesk and Freshdesk, including operations like refunds within configured limits.
The trust page states plainly that customer data never trains public models, which is the single most important sentence for any team weighing whether to pipe real support transcripts into a third-party agent. The company also describes processing personal data only as instructed by the data controller and supporting data subject access requests.
On the security side the company states GDPR compliance, alignment with SOC 2 Type II standards, infrastructure built to ISO 27001, AES-256 encryption at rest and TLS 1.3 in transit. Role-based access control is available on all plans, with SSO through SAML 2.0 and OAuth 2.0, and Enterprise customers can request private cloud deployment in specific regions for data residency.
The platform markets setup in minutes for basic configurations, and the enterprise evaluation path is framed as days rather than months. Realistically, connecting systems and configuring guardrails is quick, but tuning knowledge and validating accuracy before granting full autonomy takes longer.
Yes. An Enterprise Sandbox runs your company's and industry's workflows and terminology using synthetic data only, producing a stakeholder-ready brief of outcomes without touching real records — useful when security review blocks conventional pilots.
Both are addressed, but the fit differs. Small teams can start on the free or Pro tiers self-serve, while dialect tuning, custom personas, unlimited seats, the sandbox and a dedicated success manager are reserved for Enterprise agreements.
It escalates to a human with the accumulated context rather than dead-ending the conversation, and human-in-the-loop approvals can be required for sensitive actions. Reviewing escalations regularly is the recommended way to find gaps in the agent's knowledge.
