Product Overview

1. What is the main highlight of Fini’s November 2024 product update?
The November 2024 update introduces Fini 2.0, featuring a refreshed user interface, an intuitive Prompt Builder for seamless prompt creation, and powerful configuration enhancements to improve AI agent performance and user experience.

2. How does Fini 2.0 improve the AI configuration experience?
Fini 2.0 streamlines AI setup by simplifying the configuration panel, improving navigability, and offering better visibility into prompt structure, knowledge connections, and real-time testing, making it easier for teams to fine-tune agent behavior.

3. What is the Prompt Builder introduced in this update?
Prompt Builder is a new tool in Fini that lets users craft, test, and deploy AI prompts in a user-friendly interface without writing any code. It simplifies creating nuanced instructions that shape AI responses according to brand tone and support logic.

4. Why was the Fini interface redesigned in 2.0?
The redesign aims to improve clarity, usability, and speed, allowing users to manage knowledge, analytics, and configurations from a single, intuitive workspace—reducing friction in maintaining and scaling AI agents.

5. What industries benefit most from these updates?
E-commerce and SaaS companies with dynamic support environments gain the most, as the updates empower faster onboarding, deeper automation, and tailored agent behavior—especially in high-volume ticket scenarios.

Prompt Builder

6. How does the new Prompt Builder work?
The Prompt Builder provides a guided interface to input prompt instructions, test them on sample queries, and preview AI responses instantly. Users can drag and drop context blocks, preview logic, and refine outputs quickly.

7. Who can use the Prompt Builder in Fini?
Support managers, product teams, and customer success leads—anyone responsible for managing AI tone, escalation logic, or compliance behavior—can use Prompt Builder without needing technical skills.

8. What kind of prompts can be created using this tool?
Users can create prompts for brand tone, compliance responses, escalation guidelines, product messaging, or troubleshooting flows—tailored to any use case or user segment.

9. How does Prompt Builder improve collaboration between support and product teams?
With a visual, no-code interface, Prompt Builder allows both support and product stakeholders to align on AI behavior, review prompt logic, and co-create flows that reflect accurate, brand-safe messaging.

10. Can I A/B test prompts using this tool?
While native A/B testing isn’t launched yet, Prompt Builder allows instant previewing of different prompt versions, helping teams evaluate variations before deploying them live.

Knowledge Base Improvements

11. What knowledge-related improvements were announced in the update?
Fini now supports knowledge creation directly from past conversations. It identifies support messages that resolved user issues, filters out noise or incorrect content, and converts them into actionable knowledge items.

12. How does Fini clean and refine knowledge from past conversations?
Fini uses AI to extract only the helpful, accurate portions of past ticket threads, removing outdated or conflicting advice, and automatically enriching your knowledge base with trusted, validated content.

13. Why is Fini’s approach to knowledge creation different?
Unlike systems that blindly ingest chat transcripts, Fini understands context, relevance, and tone—allowing it to build structured, clean knowledge from support history with minimal human intervention.

14. Does this feature support multilingual knowledge extraction?
Yes, Fini can extract and generate knowledge from multilingual chat histories, making it ideal for global companies that need consistent knowledge base content across languages.

15. Can teams edit AI-generated knowledge before publishing it?
Absolutely. Human review is encouraged. AI-generated articles are editable within Fini’s Knowledge Hub, allowing support teams to adjust tone, update language, or add examples before publishing.

Human-in-the-Loop Feedback

16. What is the Human-in-the-Loop feedback feature in Fini?
When the AI fails to answer a query due to missing information, Fini flags the case for human review. Once a support agent responds, that response is automatically added to the knowledge system, improving future coverage.

17. Why is this feedback loop critical for AI learning?
It ensures the AI never misses the same question twice. This loop allows the AI to continuously improve from real-world edge cases while keeping human oversight and control intact.

18. How does this reduce knowledge gaps over time?
Every flagged query and human-provided answer helps fill blind spots in the AI’s understanding, resulting in a progressively more accurate, responsive, and comprehensive support system.

19. Who benefits from the Human-in-the-Loop process?
Support teams gain confidence that their input improves the AI, while customers experience fewer “I don’t know” responses over time. It builds trust, accuracy, and efficiency across the board.

20. How does this process align with product changes?
As your product evolves, so does your support. Human-in-the-Loop ensures new features, policy updates, or edge case clarifications get documented and reflected in the AI’s behavior immediately.

Case Study – Qogita Success

21. What challenges did Qogita face before using Fini?
Qogita, a fast-scaling e-commerce brand, faced high support volumes around order tracking, shipping, and product availability. Their team struggled to maintain SLA and deliver real-time updates at scale.

22. How did Fini integrate with Qogita’s existing tools?
Fini integrated with Qogita’s HubSpot CRM and backend order APIs, enabling seamless access to customer data and real-time order status for instant, accurate responses through AI.

23. What were the measurable outcomes of using Fini at Qogita?
Qogita achieved 88% end-to-end ticket resolution via Fini, improved SLA performance by 121%, and maintained over 90% response accuracy according to manual QA reviews.

24. How did Fini impact Qogita’s support team productivity?
By offloading routine tasks like order updates, Fini freed up agents to focus on complex issues. This not only boosted agent efficiency but also improved team morale and responsiveness.

25. What feedback did Qogita provide about AI agent performance?
Their team highlighted how small tweaks to knowledge items led to noticeable performance gains, reinforcing Fini’s adaptive and feedback-friendly design.

Upcoming Features

26. What’s next in Fini’s product roadmap?
Fini is launching auto-generated knowledge from synced tickets and expanding Human-in-the-Loop tools for even faster coverage of unknown queries, ensuring your AI evolves with your product.

27. How will synced ticket history improve knowledge generation?
Fini will analyze resolved tickets from your support tools, identify the resolution steps, and convert them into structured, reusable knowledge content automatically.

28. Will there be deeper reporting around feedback loops?
Yes, upcoming updates include analytics on feedback loop performance—showing which queries were flagged, what was learned, and how the AI coverage improved over time.

29. How does Fini plan to improve accuracy and coverage over time?
Fini combines human feedback, real user conversations, and pattern analysis to automatically expand coverage, refine tone, and boost response quality across channels.

30. Is there a timeline for releasing the new knowledge sync features?
While no exact date is provided, the blog indicates these features are coming next, likely within the next product cycle, suggesting high prioritization on the roadmap.

Deployment & Customization

31. How quickly can companies deploy these new features?
Most features—including Prompt Builder and Fini 2.0 UI—are live and ready to use today. Deployments can happen within hours for existing users, and new customers can onboard within a week.

32. Is Fini’s platform customizable for different support models?
Yes, Fini offers flexible configuration for B2B, B2C, SaaS, and e-commerce models. Users can customize prompts, knowledge visibility, escalation paths, and user attributes.

33. Can customers control which prompts or flows are active?
Absolutely. Each prompt can be toggled, scoped to segments, or linked to specific user flows, ensuring the right logic is used for the right customer scenario.

34. Does Fini support multi-language prompt configuration?
Yes, you can configure language-specific prompts or deploy multi-lingual agents using Fini’s language detection and context handling systems.

35. How secure is user data in the Prompt Builder and feedback loops?
Fini maintains enterprise-grade security, including PII redaction, encrypted storage, audit logs, and access controls to ensure prompt data and customer inputs remain protected.

Business Impact

36. How does this update improve customer satisfaction?
With faster, more accurate answers, personalized logic, and fewer “I don’t know” replies, customers enjoy a smoother support experience—driving higher CSAT and retention.

37. What is the impact on agent productivity?
Fini’s updates reduce agent time spent on repetitive queries and configuration tasks, allowing teams to shift focus to strategic improvements and complex resolutions.

38. How do these changes help reduce support costs?
By automating routine tasks, minimizing escalation rates, and increasing AI resolution rates, Fini helps businesses lower operational costs without compromising quality.

39. How does Prompt Builder contribute to brand consistency?
By centralizing prompt logic and allowing preview and review of AI tone, Prompt Builder ensures all AI outputs align with the company’s brand voice, legal language, and CX strategy.

40. Why should businesses adopt Fini’s AI now?
With rising customer expectations and the growing need for scalable, empathetic support, Fini’s AI—especially with this update—offers a future-ready platform that turns support from a cost center into a competitive advantage.