Agent

What is Agent.ai

Agent.ai is a platform for building, deploying, and operating AI-powered conversational agents that connect to an organization’s data and business systems. The platform focuses on conversational workflows for customer support, sales assist, and internal knowledge tasks, combining natural language understanding, retrieval from private knowledge bases, and connectors to common business tools. Agent.ai targets product teams, customer success and support groups, and engineering teams that want production-grade virtual assistants with analytics and operational controls.

Agent.ai bundles three core capabilities: a conversation engine with NLU and dialogue management, a knowledge retrieval layer that indexes documents and structured data, and integrations to business tools (CRM, helpdesk, file storage). The platform includes both no-code flows for business users and an API/SDK surface for developers who want to embed agents in apps or orchestrate multi-step automations.

Technical audiences find Agent.ai useful for running controlled AI assistants that respect data access rules and provide observability. Non-technical teams use the visual builder and prebuilt templates to define common support workflows—like refund processing, FAQ automation, or lead qualification—while engineers extend capabilities with custom actions and third-party integrations.

Agent.ai features

What does agent.ai do?

Agent.ai builds conversational agents that answer questions, perform actions, and automate routine tasks by combining language models with structured business logic. The platform performs semantic search over private documents and knowledge bases, routes complex queries to human agents, and triggers API calls or backend workflows when needed.

Key runtime features include session state management, context-aware responses, fallback routing to humans, and conversation analytics. For deployment, Agent.ai supports web widgets, embeddable chat components, and messaging channel integrations so agents can operate on websites, mobile apps, and collaboration platforms.

Developer-facing features include an HTTP REST API, WebSocket streaming for low-latency responses, SDKs for common languages, and webhook/action handlers that let the agent call external services. There are also monitoring tools for errors, conversation transcripts, and usage metrics.

Agent.ai pricing

Agent.ai offers these pricing plans:

• Free Plan: $0/month with limited conversations, developer sandbox, and basic community support
• Starter: $29/month per seat (billed monthly) or $24/month per seat (billed annually) with higher usage quotas, standard integrations, and email support
• Professional: $99/month per seat (billed monthly) or $79/month per seat (billed annually) with advanced analytics, SLA-backed uptime, and advanced connectors
• Enterprise: Custom pricing for large deployments, SSO, dedicated support, on-prem or VPC options, and compliance add-ons

Check Agent.ai's current pricing tiers (https://www.agent.ai/pricing) for the latest rates and enterprise options.

Agent.ai’s billing model is typically per-seat combined with metered conversation or token usage for high-volume deployments. Annual billing reduces the per-seat rate and may include implementation credits and a service-level agreement for uptime and support response times.

The Free Plan is intended for evaluation and proof-of-concept work; it includes limited API calls and smaller document indexing quotas. The Starter tier is designed for small teams automating basic support flows, while Professional adds business-grade features and larger indexing and throughput allowances. Enterprise pricing is negotiated and often includes custom integrations, compliance work, and higher throughput guarantees.

How much is agent.ai per month

Agent.ai starts at $29/month per seat when billed monthly for the Starter plan. The Professional plan is $99/month per seat on a monthly billing cycle. Enterprise pricing varies based on contract size and feature needs.

How much is agent.ai per year

Agent.ai costs $288/year per seat for the Starter plan when billed annually at the discounted $24/month per seat rate. The Professional plan billed annually is $948/year per seat at the $79/month per seat rate. Enterprise annual contracts are quoted and billed under custom terms.

How much is agent.ai in general

Agent.ai pricing ranges from $0 (free) to $99+/month per seat. Small teams can begin at the Free or Starter tiers; production customer support deployments commonly fall into the Professional or Enterprise bands where custom SLAs, advanced integrations, and higher throughput are required.

Total cost of ownership depends on indexed document volume, integration complexity, message/conversation volume, and whether you require on-prem or VPC deployment for compliance. For an accurate estimate, consult Agent.ai’s sales team or view Agent.ai's current pricing tiers (https://www.agent.ai/pricing).

What is agent.ai used for

Agent.ai is used to automate conversational workflows that previously required human agents or scripted bots. Common use cases include customer self-service (answering product FAQs, order status), agent assist (suggesting responses and knowledge articles to support reps), and internal help desks (IT support, HR queries). The system reduces time-to-resolution by retrieving precise answers from product documentation, tickets, and CRM data.

Sales and lead qualification teams use Agent.ai to pre-qualify leads, gather contact information, and book meetings using calendar integrations. Product and engineering teams use it as an embedded assistant for developer documentation, runbooks, and internal knowledge retrieval to speed onboarding and incident response.

Operationally, Agent.ai is used to offload repetitive tasks such as password resets, status checks, and refund processing. With its action handlers, the agent can take authenticated actions (create tickets, update CRM records) which turns conversations into end-to-end automated workflows.

Pros and cons of agent.ai

Agent.ai provides a comprehensive platform for enterprise conversational AI, but there are trade-offs users should evaluate. Pros include fast prototyping with a visual builder, strong retrieval over private data sources, and production features like analytics, routing, and SLAs for the paid tiers. It also supports developer extensibility through APIs and webhooks, which makes it suitable for complex integrations.

On the downside, advanced customization typically requires engineering effort, especially for complex authentication flows or bespoke enterprise connectors. High-volume deployments can incur significant metered costs depending on conversation volume and model usage. Organizations with strict on-premise requirements may need Enterprise plans to meet compliance and hosting constraints.

Another consideration is vendor lock-in: heavy investment in Agent.ai’s conversation definitions and action handlers may require migration planning if you later change platforms. Finally, while the Free Plan is useful for evaluation, it may be too limited for realistic production testing.

Agent.ai free trial

Agent.ai provides a Free Plan intended for evaluation and small-scale POCs, and typical paid tiers include a trial period or credit for testing Professional features. The Free Plan includes a sandbox environment, basic knowledge indexing, and developer API access so teams can validate capabilities without immediate cost.

During trial periods, you can test integrations, import documents, and evaluate conversation routing and analytics. Trials are particularly useful for measuring the accuracy of knowledge retrieval on your own content and for validating end-to-end actions such as ticket creation and CRM updates.

If you need extended evaluation or production pilots, Agent.ai’s sales and customer success teams commonly offer time-bound trial extensions or pilot contracts that include support hours and onboarding assistance. Check Agent.ai's trial and demo options (https://www.agent.ai/contact) for current offerings.

Is agent.ai free

Yes, Agent.ai offers a Free Plan intended for evaluation and developer experimentation. The Free Plan includes limited conversations, restricted knowledge indexing, and community support but does not include enterprise SLAs or high-throughput quotas. For production usage, the Starter or Professional plans are recommended.

Agent.ai API

Agent.ai exposes a RESTful API and streaming interfaces for real-time conversational interactions. The API supports creating and managing agents, submitting user messages, retrieving conversation histories, indexing documents, and invoking custom actions. Authentication is handled via API keys or OAuth for server-to-server integrations.

Key API capabilities include: document ingestion endpoints for PDF/HTML/CSV sources, semantic search and retrieval endpoints (query with context), conversation endpoints for sending and receiving messages (with streaming for partial responses), and action/webhook endpoints for invoking external systems. The platform also supports webhooks for event notifications (conversation completed, escalation, or error events).

Rate limits and token-based model usage apply; larger volume customers typically move to Professional or Enterprise tiers that include higher rate limits and predictable pricing. Developers can use SDKs for Node.js and Python, or call the HTTP endpoints directly. For implementation details and full API reference, consult Agent.ai's API documentation (https://www.agent.ai/docs).

10 Agent.ai alternatives

• Slack — team collaboration platform with bots and app integrations, useful as a channel for simple conversational bots
• Microsoft Teams — enterprise collaboration with bot framework and deep Office 365 integration for internal assistants
• Intercom — customer messaging platform with conversational bots and business automation for sales and support
• Drift — conversational marketing and sales assistant focused on lead qualification and routing
• Zendesk — customer support platform with AI-powered Answer Bot for self-service
• Freshdesk — helpdesk platform with automation and chatbot integrations to offload support
• Ada — customer service automation platform focused on no-code chatbot building for support teams
• HubSpot — CRM with chatbot builder and conversational tools for sales and marketing
• Kustomer — customer service CRM with built-in automation and conversational workflows
• Gong — conversational analytics and AI assistant for sales coaching (complements rather than replaces agents)

Paid alternatives to agent.ai

• Intercom: Omnichannel customer messaging with bots and product tours, priced per active user and feature bundles. Intercom targets both sales and support use cases and includes CRM-like features for conversational marketing.

• Drift: Focused on conversational marketing and sales; its bots qualify leads and route high-value prospects to sales reps. Pricing scales with the number of seats and the volume of conversations.

• Zendesk: Offers an AI-powered Answer Bot and robust ticketing for enterprise support teams. Zendesk is broadly used for large support centers and integrates with a wide ecosystem of apps.

• Ada: No-code automation focused on self-service; Ada is popular for enterprise customer support automation and supports multi-language deployments.

• Kustomer: Built as a customer service CRM with automation and workflow capabilities, Kustomer integrates conversational channels into a unified customer record.

Open source alternatives to agent.ai

• Rasa: Open source conversational AI framework for building custom assistants with full control over NLU, dialogue management, and deployment. Rasa is suitable when you need on-premise hosting and complete customization.

• Botpress: Modular open source bot-building platform with a visual flow builder and NLU. Botpress is useful for teams that want a developer-friendly, self-hosted solution.

• Chatwoot: Open source customer engagement suite with chat and automation features; can be extended with custom bots and connectors for knowledge retrieval.

• DeepPavlov: An open source conversational framework and set of pretrained models for building task-oriented assistants and QA systems.

• Haystack (deepset): Open source framework for building search and QA systems over documents; often used as the retrieval layer in custom conversational stacks.

Frequently asked questions about Agent.ai

What is Agent.ai used for?

Agent.ai is used for building and running AI-powered conversational agents across customer support, sales, and internal knowledge workflows. Organizations deploy Agent.ai to automate FAQs, qualify leads, assist agents with suggested responses, and run internal help desks. The platform connects to document stores and business systems so agents can retrieve accurate, context-aware information.

Does Agent.ai offer an API for developers?

Yes, Agent.ai provides a RESTful API and SDKs for common languages. The API supports message handling, document ingestion, semantic search, and action invocation via webhooks. Developers use the API to embed agents in apps, stream responses, and implement custom connectors.

How much does Agent.ai cost per seat?

Agent.ai starts at $29/month per seat on the Starter plan when billed monthly; the Professional tier is $99/month per seat on monthly billing. Annual billing lowers per-seat rates to $24/month (Starter) and $79/month (Professional). Enterprise pricing is quoted.

Is there a free version of Agent.ai?

Yes, Agent.ai has a Free Plan that includes a sandbox environment, limited conversations, and basic indexing for testing and small-scale evaluations. It is intended for POCs and developer experimentation rather than production workloads.

Can Agent.ai connect to Slack and Microsoft Teams?

Yes, Agent.ai integrates with collaboration platforms like Slack and Microsoft Teams. These integrations allow agents to operate inside team channels, send proactive messages, and escalate to human agents while preserving conversational context.

How does Agent.ai handle customer data and compliance?

Agent.ai supports enterprise compliance controls including SSO and VPC/on-premise deployment options on Enterprise plans. The platform offers role-based access, audit logs, and controls for data retention and redaction; customers with specific regulatory needs can negotiate deployment and contractual protections.

Can Agent.ai perform actions like creating tickets or updating CRM records?

Yes, Agent.ai supports action handlers and webhooks for executing backend tasks. Agents can call authenticated APIs to create tickets, update CRM fields, or trigger workflows in external systems when a user requests an action that requires state change.

Does Agent.ai support private document search and knowledge bases?

Yes, Agent.ai includes a knowledge retrieval layer for indexing private documents and structured data. The platform performs semantic search over PDFs, knowledge bases, and internal docs, and can be configured to prioritize trusted sources and provenance for answers.

How scalable is Agent.ai for high-volume support centers?

Agent.ai scales to handle high-throughput conversational workloads under Professional and Enterprise plans. Higher tiers include increased rate limits, SLA-backed uptime, and options for dedicated infrastructure to meet throughput and latency requirements for large contact centers.

What training and support resources are available for Agent.ai?

Agent.ai provides documentation, developer guides, and tiered support plans. The Free Plan includes community support and docs; paid plans add email or phone support, onboarding assistance, and enterprise customers receive dedicated customer success resources and training as part of their contract.

agent.ai careers

Agent.ai hires across product, engineering, sales, and customer success roles. Job listings typically appear on the company’s careers page and LinkedIn where they post openings for machine learning engineers, backend developers, and solutions architects. Candidates with experience in NLP, data engineering, and SaaS operations are commonly sought.

agent.ai affiliate

Agent.ai runs partnership and referral programs for agencies and system integrators that implement the platform for customers. Affiliate or reseller terms vary; partners typically receive margin on seats sold and implementation credits for joint sales opportunities. For program details, check Agent.ai's partner information (https://www.agent.ai/partners).

Where to find agent.ai reviews

You can find user reviews and comparisons on software review sites like G2 and Capterra, and in technical write-ups on developer blogs and community forums. For the most current feedback and case studies, consult Agent.ai’s customer testimonials and independent reviews on software marketplaces.