Audit & ticket mapping
Mapped a year of resolved tickets against the product docs to find exactly which repeat questions were costing agents the most time.
IT & TECH · CASE STUDY
NimbusSoft now auto-solves 70%
A RAG support copilot grounded in their docs that now resolves 70% of tickets automatically.
- 10 weeks to production
- Grounded in real docs
- Confidence-based handoff
NimbusSoft Live70%tickets auto-solved
Capabilities
Grounded answers
Full ticket automation
Confidence-based handoff
Helpdesk-native
The auto-triaged ticket queue
Every ticket the moment it lands — grounded in real docs, resolved or handed off with full context.
LIVE QUEUE — AUTO-TRIAGEDAUTO-REFRESH
TCK-6621API rate limit errorGrounded in docs · resolved automaticallyAUTO-RESOLVED< 1 min
TCK-6619Billing discrepancyLow confidence · needs agentESCALATED2 min
TCK-6614SSO login failureGrounded in docs · resolved automaticallyAUTO-RESOLVED9 min
TCK-6608Webhook not firingMatched similar past ticketPENDING23 min
Every answer traces back to a real doc or past ticket — uncertain cases hand off to a human with full context.
Why NimbusSoft called us
Support volume was growing faster than headcount, and most incoming tickets were repeat questions already answered somewhere in the product docs — but customers couldn't find the answer themselves and agents spent most of their day re-explaining the same fixes.
Resolve repeat support tickets automatically, grounded in real docs, without a support headcount increase.
10 weeks to productionTimeline
AI engineers + support ops leadTeam
From audit to production
Why 10 weeks was realistic — the scope was one copilot grounded in existing docs, not a helpdesk migration. Here's the breakdown:
RAG build & grounding
Built the retrieval layer over NimbusSoft's own docs and resolved tickets, so every answer traces back to a real source.
Helpdesk integration
Wired the copilot directly into the existing support tool — no new interface for agents or customers.
Live rollout & tuning
Rolled out with confidence-based handoff from day one, then tuned the threshold on real resolution outcomes.
What we delivered
The stack behind NimbusSoft's grounded support copilot.
Retrieval-augmented answer generation
Every question is embedded and matched against a vector index of NimbusSoft's own docs and resolved tickets; the model only answers from what it actually retrieves, with a confidence threshold gating the handoff to a human agent instead of guessing.
Python
Hugging Face
FastAPI
Elasticsearch
PostgreSQL
Redis
Docker
Zendesk integration
Plus a full vector index over NimbusSoft's docs and ticket history — the connective work most off-the-shelf chatbots skip.
The challenge
Support volume was growing faster than headcount, and most incoming tickets were repeat questions already answered somewhere in the product docs — but customers couldn't find the answer themselves and agents spent most of their day re-explaining the same fixes.
What we built
We built a retrieval-augmented support copilot grounded directly in NimbusSoft's own documentation and past resolved tickets, so every answer traces back to a real source instead of a hallucinated guess, with a clean handoff to a human agent for anything the model isn't confident about.
Core capabilities
RAG
Grounded answers
Every response traces back to a real doc or past ticket — no hallucinated fixes.
AUTO
Full ticket automation
Resolves the routine 70% end to end, not just first-response drafting.
CONF
Confidence-based handoff
Uncertain cases route to a human agent with full context attached, not a blank slate.
HD
Helpdesk-native
Works inside the existing support tool — no new interface for agents or customers.
Inside the copilot
The ticket queue support agents use every shift, from sign-in to escalation log.
Main feature — a ticket answered, grounded, sourced, sent
Dashboard — resolution rate & CSAT
Login — support team access
Detail — confidence gauge and the sourced answer
Escalation log — handoffs to human agents
The outcome
70% of inbound tickets are now resolved automatically end to end, freeing the human team to focus on the harder 30% instead of repeat questions.
70%tickets auto-solved
10weeks to production
3AI systems shipped
What the support team is saying
Straight from the team fielding tickets every day.
“Most of our ticket volume was the same rate-limit and SSO questions answered somewhere in our docs that customers never found. Bounce's copilot is grounded in those exact docs and past tickets so it isn't guessing — every answer cites its source and anything it's not confident about lands with a human and full context attached. My team stopped re-typing the same three answers a hundred times a day.”
Daniel ChoHead of Customer Support, IT & TechFrequently Asked Questions
Every response is grounded in a real doc or a real past resolved ticket — if it can't find a confident source, it hands off to a human instead of guessing.
Those tickets route straight to a human agent with full context already attached — the conversation, the sources it checked, and its confidence score.
Yes — it runs inside the existing support tool. No new interface for agents to learn or for customers to find.
10 weeks from kickoff to production, covering the RAG copilot build and helpdesk integration — not a proof of concept.
No — it removes the repeat-question load. Agents spend their time on the harder 30% that actually needs a person, not re-explaining the same fix all day.
◆ Let's build
Ready to put AI to work in your industry?
Tell us your challenge. We'll come back with a concrete, no-obligation plan and a live demo of what's possible for your team.
- Free AI auditWe map the highest-ROI AI opportunities across your workflows.
- Prototype in weeksA working proof-of-concept on your real data before you commit.
- One accountable teamStrategy, models, data and deployment — end to end.
120+ teams shipped across 6 industries
Book a free demo
Reply within 1 business day · No obligation.