Boost.ai
Bot platforms software
Chatbots software
AI chatbots software
Customer self-service software
Conversational support software
Customer service automation software
Agentic AI software
AI agent builders software
AI voice assistants
Conversational intelligence software
Generative AI software
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
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- Banking and insurance
- Energy and utilities
- Public sector and nonprofit organizations
What is Boost.ai
Boost.ai is an AI chatbot and conversational automation platform used to deliver customer self-service across digital channels. It supports building and operating virtual agents for customer service teams, typically in regulated or high-volume support environments. The product combines intent-based conversation design with generative AI capabilities and integrations to backend systems for case handling and knowledge retrieval. It is used by organizations that want to deflect routine inquiries while maintaining escalation paths to human agents.
Enterprise self-service focus
Boost.ai is designed around customer support automation use cases such as FAQs, account and service inquiries, and guided workflows. It supports operational needs like analytics, conversation monitoring, and continuous improvement processes that customer service teams typically require. This positions it well for organizations prioritizing deflection and consistent service experiences over purely sales-led chat.
Hybrid NLU and GenAI
The platform supports structured intent-based flows alongside generative AI features, which can help balance controllability with broader language coverage. This hybrid approach can reduce failure modes common in purely generative experiences for customer support. It also enables teams to keep high-risk topics in deterministic flows while using generative responses where appropriate.
Omnichannel and escalation support
Boost.ai supports deployment across common digital channels and provides mechanisms to hand off conversations to human agents when automation is insufficient. This is important for customer service operations that need continuity between bot and agent experiences. It also enables organizations to standardize conversational behavior across channels rather than managing separate bot implementations.
Implementation requires governance
Deploying customer-service-grade automation typically requires content ownership, conversation design, and ongoing tuning. Organizations without clear knowledge management and support process governance may struggle to achieve stable outcomes. The effort can be higher when integrating with multiple backend systems and policies.
Complexity for small teams
The platform’s enterprise feature set can be more than what small businesses need for simple lead capture or lightweight chat. Teams seeking a minimal setup may find configuration, analytics, and lifecycle management heavier than simpler chatbot tools. Total cost and time-to-value can be less favorable for low-volume use cases.
GenAI risk management needed
Using generative AI in customer support introduces requirements for response control, grounding, and compliance review. Organizations may need additional safeguards such as approved knowledge sources, testing, and monitoring to reduce hallucinations or policy violations. These controls can limit how broadly generative responses are used in production.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| Custom / Enterprise | Not publicly listed — pricing available on request (contact sales / book a demo) | boost.ai is positioned as an enterprise conversational AI platform (chat + voice, hybrid AI, integrations, security/compliance). No public tiered or usage prices are published on the official site; customers are invited to contact sales or book a demo for quotes. |
Seller details
boost.ai AS
Oslo, Norway
2016
Private
https://boost.ai/
https://x.com/boostai
https://www.linkedin.com/company/boost-ai/
