Automating Ticket Resolution with AI-Powered Resolvify++

Client Overview

At Sigma Infosolutions, we believe that if you’re going to build a rocket, you should be the first to ride it. That’s exactly what we did with Resolvify++, our in-house AI-powered platform designed to revolutionize how our support team resolves Freshdesk tickets across multiple tenants.

Built not just for the sake of innovation, but out of real operational necessity, Resolvify++ started as a practical answer to a burning question:

“How can we reduce support chaos and let AI do the heavy lifting—without sacrificing accuracy or control?”

Project Brief

The goal was clear: eliminate ticket clutter, enhance response quality, and let our agents spend time where it really matters—on complex queries that need a human touch. We aimed to build a two-pronged system:

Resolvify: An intuitive interface for agents to fetch AI-generated replies, explore past resolutions, and fine-tune suggestions.
Resolvify++: A background automation engine that acts like a silent ninja—categorizing, resolving, or escalating tickets in real time, all powered by Freshdesk webhooks and smart thresholds.

The result? A support system that learns, adapts, and works around the clock.

Business Needs And Challenges

Before Resolvify++ was born, our support landscape looked more like a jigsaw puzzle with missing pieces:

Wild West Ticket Formats: Tickets came in every shape and size—messy HTML, sparse descriptions, or cryptic comments. Extracting meaningful signals from that noise wasn’t just tough; it was a gamble.
Confidence Scoring Dilemmas: How do you trust AI to auto-resolve a ticket without fear of it backfiring? Getting confidence thresholds just right was like tuning a violin—it had to be precise.
Juggling Multiple Tenants: Each client (tenant) needed a walled garden—isolated storage, specific formatting, and custom workflows. One-size-fits-all simply wasn’t an option.

High-Stakes Integrations: With Freshdesk and Playbook in the loop, timing was everything. If a webhook missed its mark or a payload was off, SLAs would slip, and alerts would fly.
Incomplete Data = Dead Ends: Half-baked tickets stalled progress. We needed a mechanism that didn’t just throw up its hands when details were missing—but instead paused, asked for more, and resumed seamlessly.
Evolving Knowledge: Support doesn’t stand still. Capturing agent feedback and updating our knowledge base across tenants, without creating chaos or duplicates, was a must-have.

Solutions

So, we rolled up our sleeves, cracked open the toolbox, and began crafting a system that learns, listens, and leads.

Cleaning the Mess Before the Magic – We began by cleaning ticket content like a chef preps their kitchen—sanitizing HTML, validating inputs, and baking in fallback logic.
Confidence Scoring with Vector Search – Using Qdrant vector search and SentenceTransformer embeddings, we created a smart matching engine. Only when the AI was truly sure—above a tenant-specific threshold—did it swing into auto-resolution mode. Otherwise, it logged the case for review and learning.
Tenant-Centric Architecture – Every tenant gets its own data collection and config hub. From routing logic to formatting rules, we made the platform as flexible as a yoga instructor and as secure as a vault.

Real-Time Freshdesk & Playbook Integration – We didn’t just plug into Freshdesk—we danced with it. Tickets triggered actions, Playbook handled task automation, and fallback scenarios sent Squadcast alerts when things got hairy.
Partial Data? No Problem. – We introduced a two-step process for missing info:
- Ask for what’s missing.
- Resume automation, the moment we get it.
- Think of it like putting a puzzle on pause until you find that final piece.
Feedback That Fuels Growth – Agents could review, tweak, and even rewrite AI suggestions. These edits were saved back to the knowledge base, helping Resolvify++ learn like a straight-A student with perfect memory.

Benefits

The proof is in the performance—Resolvify++ didn’t just tick boxes, it rewrote the playbook.

50%+ Faster Resolutions: Routine tickets vanished like smoke—auto-resolved within seconds. Complex ones got faster, context-rich handling. Less waiting, more winning.
Cleaner Coverage, Fewer Gaps: By pulling from historical context, AccelTest ensures consistent coverage—no more forgotten edge cases or duplicate test logic.
Personalized QA Workflows: Each tenant runs their own version of the platform, complete with tailored test libraries and reusability built in.

Continuous Learning on Autopilot: With every tweak and bit of feedback, Resolvify++ got sharper, smarter, and more tenant-aware. It wasn’t just a system—it became a teammate.
Scalability Built In: From onboarding new tenants to ingesting fresh documents, Resolvify++ scaled like a champ—without breaking a sweat.
Happier Clients, Smoother Ops: Quick turnarounds, reliable answers, and proactive updates meant one thing: happier clients who trust our support like a lifeline.

Tools & Technologies

Frontend: HTML, CSS, JavaScript	Backend: Python (Flask)
AI: Claude (Anthropic API), Sentence Transformers	Vector DB: QDrant Cloud
User Management: PostgreSQL	APIs: Freshdesk, SquadCast
Secrets: AWS Secrets Manager

Turning Tickets into Triumphs

Resolvify++ didn’t just solve a technical problem—it transformed how we think about support. By blending AI with human oversight, we built a solution that’s always learning, always improving, and always ready to take on the next support curveball.

If you’re looking to tame your ticket chaos, reduce support fatigue, and delight customers with lightning-fast answers, let’s talk.

Sigma Infosolutions knows how to turn support from a pain point into a competitive edge.

Resolvify++ Case Study - AI-powered Freshdesk Tickets

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