Number of Seats/Users: {post.post_title} 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 {post.post_title} 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 {post.post_title}. {post.post_title} reserves discounts for new customers or those not currently under promotional pricing.

Volume or Usage Commitment: {post.post_title} 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 {post.post_title}. Such companies are often in a position to negotiate for better pricing.

Early Renewal or Prepayment: {post.post_title} 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 Unifai is delivering strong value for teams struggling with messy product data and tight go‑to‑market timelines.

Overall sentiment from Spendbase clients is very positive, with particular emphasis on speed, ease of use, and support quality.

Key strengths our clients highlight:

• Time-to-market & productivity
• Classification time often cut by about 50%.
• Faster onboarding of thousands of SKUs from hundreds of suppliers.

• Quick first results after deployment, without heavy setup.

• Data quality improvements

• Better product categorization into existing nomenclatures.
• Strong capabilities for:
  • Categorization
  • Mapping different file formats
  • Attribute extraction and enrichment

• Noticeable reduction in:

  • Duplicates
  • Missing attributes
  • Classification errors

• Business impact

• More reliable product data feeding e‑commerce and marketplace channels.
• Better basis for analyzing customer behavior and running targeted actions.

• Direct contribution to higher conversion potential thanks to cleaner, richer product info.

• User experience & implementation

• Described as simple, intuitive, and easy to deploy.
• Can be interfaced with existing internal tools.

• Quick adoption by teams, even non-technical ones.

• Support & partnership

• Unifai’s team is seen as very reactive and effective.
• Ongoing guidance during initial setup and daily use.

Main areas for improvement our clients mention:

• AI reliability
• Already “very interesting” accuracy, but expectations are for even higher precision over time.

• Some clients see this as a natural learning curve rather than a blocker.

• Ergonomics / UX

• The solution is still evolving; interface and ergonomics could be refined further.

From a Spendbase discount perspective, this pattern is clear: teams that deal with large product catalogs and multi-supplier feeds tend to see rapid ROI with Unifai. The biggest gains come from reduced manual work, faster catalog readiness, and fewer data errors that would otherwise impact sales.