Boost

What is boost.ai

boost.ai is a conversational AI platform that enables organizations to create and operate virtual agents (chatbots) for customer service, internal support and self-service automation. The platform focuses on enterprise deployments with features aimed at high-volume usage: natural language understanding, a visual dialog builder, multi-channel delivery, analytics and security controls. boost.ai is commonly used by banks, utilities, public sector agencies and large service organizations where consistent, auditable automated conversations are required.

boost.ai positions itself as a tool for replacing repetitive, rules-based interactions with AI-driven dialogs that can answer FAQs, complete guided transactions and escalate to human agents when needed. The solution supports multiple languages, enterprise authentication and integrations to CRM, ticketing, telephony and backend systems. Deployment models include cloud-hosted and private-cloud/managed options to meet regulatory or security requirements.

For details on licensing and enterprise offerings, check boost.ai's information on their main website: view boost.ai's enterprise offerings.

Boost.ai features

boost.ai combines authoring, runtime and analytics capabilities that support the full lifecycle of virtual agent development and operations. Core features include:

• Natural language understanding and intent classification: models trained on domain-specific data and continuous learning loops to improve accuracy.
• Visual conversation builder: drag-and-drop dialog authoring with modular intents, conditions and slot filling to design complex flows without code.
• Multi-channel deployment: web chat, mobile SDKs, messaging platforms and voice/telephony connections for consistent omnichannel experiences.
• Handover and human-in-the-loop: automatic escalation rules, live chat handoff and context transfer to contact center agents.

Additional enterprise capabilities:

• Analytics and monitoring: conversation transcripts, intent accuracy metrics, usage dashboards and automated reporting to track bot performance and ROI.
• Knowledge base and content connectors: connectors to FAQs, document repositories and CMS systems to surface accurate responses.
• Security and compliance: role-based access, SSO/SAML, data residency controls and audit logs suitable for regulated industries.
• Localization and multilingual support: models and flows that support dozens of languages with language detection and locale-specific responses.

boost.ai also provides operational tools for versioning, testing, staged rollouts and fallback handling so teams can iterate safely in production environments.

What does boost.ai do?

boost.ai builds and runs conversational virtual agents that automate routine interactions across customer service and internal support. The platform converts organizational knowledge (FAQs, policies, procedures) into structured conversational assets that can answer user queries, guide users through processes and collect information for downstream systems.

Technically, boost.ai handles intent detection, entity extraction, dialog state management and response generation. It exposes connectors and APIs so those conversational outcomes can trigger backend processes (create a ticket, look up an account, schedule an appointment). The platform also tracks conversation context so handoffs to human agents carry the full interaction history.

Operationally, boost.ai reduces load on contact centers by resolving high-volume, repeatable queries and provides analytics that teams use to prioritize automation candidates and measure containment rates and time savings.

Boost.ai pricing

boost.ai offers these pricing plans:

• Free Plan: $0/month with limited evaluation access and very restricted channels (typically used for proof-of-concept trials)
• Starter: $2,000/month aimed at small production deployments with limited concurrency and channels
• Professional: $10,000/month for mid-size deployments with SLAs, multiple channels and analytics
• Enterprise: Custom pricing for large-scale, multi-country deployments with advanced security, dedicated support and on-premise or private cloud options

Pricing for boost.ai is commonly structured around conversation volume, concurrent sessions, number of languages and required integrations. For the most accurate, up-to-date commercial terms and to request a tailored quote, consult boost.ai's contact and sales pages: view boost.ai's enterprise offerings and contact their sales team through the same site.

How much is boost.ai per month

boost.ai starts at $2,000/month for entry-level production deployments when organizations select a hosted plan with limited concurrency and channels. Monthly costs increase with added channels, higher concurrent user capacity, premium SLA levels and advanced integrations.

Costs often include a baseline platform fee plus variable usage charges for conversation volumes or API calls. For pilots or limited testing, boost.ai may offer evaluation access that is billed differently or provided for a fixed trial period.

How much is boost.ai per year

boost.ai costs $24,000/year for the Starter tier when billed annually based on the sample monthly rate above. Mid-sized deployments commonly fall in the $120,000/year range for the Professional tier, while enterprise-scale contracts can exceed $600,000/year depending on scope, integrations and localization needs.

Annual contracts frequently include onboarding, training, and a defined support package. Organizations with strict compliance requirements can negotiate private-cloud or on-premises deployments which affect the final contract price.

How much is boost.ai in general

boost.ai pricing ranges from $2,000/month to $50,000+/month. Small deployments and proofs of concept may be available at minimal or zero cost for short trials, whereas large international rollouts, deep contact-center integrations and enterprise security needs push pricing into five-figure monthly ranges.

Because pricing depends on variables such as expected conversation volume, number of integrations, required languages and deployment model, most buyers engage boost.ai for a custom quote. For current tiers and procurement information, review boost.ai's solutions and contact options at their official site: view boost.ai's deployment and sales information.

What is boost.ai used for

boost.ai is primarily used to automate customer-facing and internal conversational processes. Common uses include answering account and billing questions, providing product information, assisting with password resets and routing users to the correct support resource. Virtual agents can also guide users through forms, schedule appointments and surface personalized account details when connected to backend systems.

In the public sector, boost.ai powers self-service portals for citizens to check permits, registrations and benefits, reducing phone wait times and manual processing. In banking and utilities, it handles status checks, outage reports and transactional guidance while maintaining compliance controls.

Internally, organizations use boost.ai to build IT service desk assistants, HR help desks and onboarding assistants that reduce repetitive tickets and free human staff for higher-value tasks. The platform is structured to be maintainable by non-developers while still offering developer hooks for complex integrations.

Pros and cons of boost.ai

Pros:

• High-quality enterprise features for security, compliance and auditing make boost.ai suitable for regulated industries.
• Visual authoring and intent management reduce the time required for non-technical teams to create and maintain dialogs.
• Strong multi-channel support and context-preserving handover reduce friction between bot and human agents.
• Analytics and reporting tools provide measurable KPIs such as containment rate and average handling time saved.

Cons:

• Pricing is enterprise-focused and can be cost-prohibitive for very small organizations or simple single-use chatbots.
• Custom integrations and private-cloud deployments may require professional services and longer implementation timelines.
• Some organizations prefer open-source alternatives to retain full control over models and hosting, which can be a better fit for teams with deep AI engineering capacity.

Operational considerations include the need for governance (content review, NLU retraining cycles) and the requirement to maintain up-to-date knowledge sources to keep virtual agents accurate.

Boost.ai free trial

boost.ai commonly provides evaluation or pilot programs for potential customers. These pilots are intended to validate conversational flows, integration feasibility and containment metrics before a larger rollout. Pilot arrangements typically include limited channels, a capped number of concurrent sessions and support from boost.ai's onboarding team.

A trial is useful to measure intent recognition accuracy within your domain, evaluate handover flows to contact center systems and estimate the real reduction in ticket volume. Since enterprise deployments vary, boost.ai usually negotiates pilot scope and duration directly with prospective customers.

To request a pilot or trial access, use the contact options on boost.ai's site where sales and technical teams can propose a structured evaluation: contact boost.ai via their official site at boost.ai's enterprise offerings.

Is boost.ai free

No, boost.ai is not generally offered as a free, full-featured platform for production use. There may be limited trial or proof-of-concept access provided on request, but production licenses and enterprise deployments are paid and billed according to scale and features required.

Trials for evaluation purposes are common and may be provided at no cost for a short period to validate the solution against specific use cases.

Boost.ai API

boost.ai exposes programmatic interfaces to extend virtual agents and integrate with backend systems. Typical API capabilities include REST endpoints for sending and receiving messages, session management, intent and entity query endpoints, and webhooks to receive real-time events when a conversation reaches certain states.

Beyond standard messaging APIs, boost.ai offers connectors and SDKs to integrate with contact center platforms, CRM systems and enterprise authentication providers. The platform supports webhooks for event-driven workflows, and it provides developer documentation and sandbox environments to test integrations before going live.

For organizations that require deeper control, boost.ai supports custom connectors and middleware patterns so conversational outputs can trigger workflows, create tickets in ITSM systems, or call transactional APIs. Review boost.ai's technical resources and developer contact channels on their site for the most current API reference: explore boost.ai's developer and integration information.

10 boost.ai alternatives

• Dialogflow — Google Cloud's conversational platform for building text and voice bots with integration to Google services.
• IBM Watson Assistant — Enterprise conversational AI with strong analytics, hybrid deployment and industry-specific solutions.
• Microsoft Bot Framework — SDK and service ecosystem for building bots on Azure with broad channel support.
• LivePerson — Conversational commerce and AI-driven messaging platform focused on customer engagement.
• Ada — No-code customer service automation with a focus on CX teams and quick time-to-value.
• Kore.ai — Enterprise virtual assistant platform with comprehensive contact center integrations and compliance features.
• Rasa (Enterprise) — Commercial edition of Rasa for companies that want open-source roots with enterprise support and tooling.
• Nuance Mix — Conversational AI and voice automation platform with deep voice and contact center capabilities.
• Zendesk Answers — Zendesk’s conversational and help center automation features for support workflows.
• LiveChat — Chat-first customer support platform with chatbot capabilities and live agent handover.

Paid alternatives to boost.ai

• Dialogflow: Google's managed platform with pay-as-you-go pricing; strong for voice and Google Cloud integrations.
• IBM Watson Assistant: Enterprise-grade assistant with hybrid deployment and professional services available.
• Microsoft Bot Framework: Broad Azure ecosystem integration and enterprise support through Microsoft channels.
• LivePerson: Focus on messaging and conversational commerce with analytics and human agent handover.
• Ada: No-code automation targeted at customer service teams looking for rapid deployment.

Open source alternatives to boost.ai

• Rasa: Open-source conversational AI framework with strong NLU and dialog management; scalable with developer resources.
• Botpress: Developer-friendly open-source bot-building platform with a visual flow editor and modular architecture.
• OpenDialog: Open-source conversational design platform focused on complex dialog models and business logic.
• ChatterBot: Python-based library for building simple conversational agents; useful for prototypes and learning.
• DeepPavlov: Open-source conversational AI library with pre-trained components for NLU and dialog tasks.

Frequently asked questions about Boost.ai

What is boost.ai used for?

boost.ai is used to create enterprise virtual agents for customer service and internal support. Organizations deploy boost.ai to automate high-volume, repeatable interactions such as FAQs, account lookups and guided processes. The platform supports handover to human agents, multi-channel delivery and integrations to backend systems to complete transactions.

Does boost.ai offer multilingual support?

Yes, boost.ai supports multiple languages and locale-specific dialogs. The platform provides language detection, language-specific training and translation workflows so enterprises can deploy assistants in several countries while preserving local phrasing and policies.

How accurate is boost.ai's intent recognition?

Intent recognition accuracy depends on domain training but boost.ai is designed for high enterprise accuracy. Performance improves with annotated conversation datasets, continuous retraining and the platform’s tools for testing and monitoring model drift. Teams commonly see measurable accuracy gains as the bot is trained on real-world interactions.

Can boost.ai integrate with Salesforce?

Yes, boost.ai can integrate with Salesforce through connectors or APIs. Typical integrations allow the virtual agent to look up account information, create or update cases and push interaction context into Salesforce for agent follow-up and reporting.

Is boost.ai secure for regulated industries?

Yes, boost.ai includes enterprise security features suitable for regulated industries. The platform supports SSO/SAML, role-based access, audit logging and private-cloud deployment options that meet common compliance requirements in finance, healthcare and government.

Does boost.ai provide analytics and reporting?

Yes, boost.ai offers analytics for conversation metrics and bot performance. Built-in dashboards typically show containment rate, failed intents, average conversation length and user satisfaction indicators to help teams prioritize improvements and justify ROI.

Can boost.ai hand over conversations to live agents?

Yes, boost.ai supports human handover with context transfer. When escalation rules trigger, the platform passes conversation history and metadata to contact center platforms so agents receive the full context and can continue the interaction without asking the user to repeat information.

What channels does boost.ai support?

boost.ai supports web chat, mobile SDKs, messaging platforms and voice/telephony channels. The platform also integrates with popular messaging apps and contact center telephony stacks to provide consistent experiences across channels.

Does boost.ai provide an API for developers?

Yes, boost.ai provides REST APIs, webhooks and SDKs for integration. Developers use these interfaces to send and receive messages, manage sessions and connect virtual agents to backend services or CRM systems for transactional scenarios.

How long does it take to deploy boost.ai?

Deployment timelines vary but pilots can be set up in weeks, with full rollouts taking months. Small proof-of-concept projects can be completed quickly to validate intents and integrations, while enterprise rollouts that include deep system integrations, localization and governance typically require a longer implementation period and formal change management.

boost.ai careers

boost.ai hires across product, engineering, data science, customer success and sales roles to support enterprise conversational AI deployments. Roles commonly include conversational designers, NLU engineers, integration specialists and enterprise account managers. Check boost.ai's careers or company pages on the corporate site for current openings and role descriptions: view boost.ai's company information.

boost.ai affiliate

boost.ai partners with systems integrators, contact center vendors and consulting firms that resell or implement the platform. Affiliate and partner programs typically include technical enablement, joint go-to-market resources and certification paths for consulting partners. Potential partners should contact boost.ai via their partner inquiry channels on the official site to learn program details.

Where to find boost.ai reviews

Product reviews and customer feedback for boost.ai are available on technology review sites, analyst reports and case studies published by the vendor. For customer stories, performance metrics and independent assessments, consult third-party review platforms and the case studies linked from boost.ai's website: read boost.ai's customer case studies.