Number of Seats/Users: Boost.AI offers discounts based on the number of users or seats. A higher volume typically leads to a better discount structure, especially for enterprise-level usage.

Commitment to a Long-Term Contract: Discounts are often provided to companies that commit to using the service for a longer period (e.g., 1-year or 3-year contracts). A longer commitment shows Boost.AI that the company is serious and willing to invest in the platform long-term.

No Active Discounts: Companies that are not already receiving other active discounts may have a better chance of qualifying for additional discounts from Boost.AI. Boost.AI reserves discounts for new customers or those not currently under promotional pricing.

Volume or Usage Commitment: Boost.AI offers discounts if you agree to a minimum amount of usage or transaction volume. This could be based on data storage, transactions, or other metrics tied to how much you will use the platform.

Enterprise-Level Negotiation: Companies that qualify as “enterprise” due to their size or complexity (e.g., having large teams, multiple departments, or geographical presence) may be eligible for additional discounts from Boost.AI. Such companies are often in a position to negotiate for better pricing.

Early Renewal or Prepayment: Boost.AI often offers discounts if you renew early or prepay for the entire contract period. This is a common approach to securing a lower price.

Here at Spendbase our internal data shows that Boost.AI is seen as a high-performing, enterprise-grade chatbot platform that delivers strong value, especially where automation and language quality really matter.

From what Spendbase clients share with us, the strongest positives cluster around:

• Ease of use and speed to value
• Non-technical teams can build and maintain bots after short training.
• Time-to-market is often measured in days or a few weeks.

• UI is described as clean, smooth, and stable.

• NLP / NLU quality

• Stand-out performance in Nordic and Baltic languages.
• Good intent recognition with advanced features like Automatic Semantic Understanding.

• Consistent, predictable responses that reduce agent workload.

• Business impact

• Noticeable reduction in contact center traffic and handling time.
• Higher self-service rates and 24/7 availability.

• Easy integrations with back-end systems allow transactional, not just FAQ, use cases.

• Enablement and support

• Strong e-learning materials and documentation.
• Very responsive partner and support teams.
• Built-in AI training tools, self-learning suggestions, and good governance controls.

At the same time, our internal data also highlights a few recurring friction points that are useful when negotiating pricing and scope:

• Analytics and measurement

• Multiple clients mention challenges around:

  • Measuring customer satisfaction directly in the tool.
  • Tracking first-contact resolution.
  • Getting deeper end-user feedback and exporting it cleanly.

• Feature gaps / roadmap

• Requests for:

  • More pre-built agents and domain modules.
  • Better multi-language and voice support.
  • Richer integrations (messengers, more open APIs).
  • Easier management when the bot grows large (intent overview, multi-tenant UI).

• Cost and enterprise-fit

• Perception that quality is high but pricing reflects that, which can be tough for smaller companies.
• Some aspects of “enterprise readiness” and roadmap communication are still maturing.

From a Spendbase discount perspective, this pattern gives leverage in a few places:
– Push for better commercial terms by pointing to missing analytics and voice/multichannel features.
– Ask for bundled services or extended trials to offset the learning and configuration effort.
– Negotiate roadmap commitments around languages, integrations, and admin tooling as part of the contract.

Net takeaway: clients are very happy with Boost.AI’s core tech and time-to-value, but there is real room to negotiate on price and extras using the gaps above.