The Challenge: 180,000 Contacts and a Contact Centre at Breaking Point
A district council serving 165,000 residents handles approximately 180,000 citizen contacts annually across phone, email, web forms, and in-person visits. Enquiry types span waste collection (missed bins, bulky waste bookings), council tax (payment plans, discounts, liability changes), housing (repairs reporting, homelessness enquiries), planning (application status, enforcement reports), and dozens of other services. The contact centre team of 18 full-time equivalents answers 70% of phone calls within 60 seconds during normal periods, but this drops to 45% during council tax billing season (February-April) when call volumes spike 40%. Average email response time has reached 5 working days, and residents complain loudly on social media about the inability to resolve simple issues outside Monday-Friday, 9-5 office hours.
The council experimented with a FAQ-based web chatbot three years ago, but its rigid keyword matching handled only 8% of enquiries successfully, and 92% of users abandoned it in frustration. Citizens need conversational AI that understands natural language, accesses their account information (council tax balance, bin collection schedule, repair status), and can transact on their behalf (book a bulky waste collection, report a missed bin, request a council tax instalment plan). Citizen data — including council tax accounts, housing records, and benefit information — must remain on UK-hosted, council-controlled infrastructure under the council’s information governance framework.
AI Solution: Transactional Council Chatbot
A self-hosted AI chatbot powered by an open-source LLM via vLLM on a dedicated GPU server handles citizen enquiries through the council website and a WhatsApp integration. The chatbot is connected to backend council systems through function calling: the council tax system for account queries and payment arrangements, the waste management system for bin schedules and missed bin reports, the housing repairs system for logging and tracking repairs, and the CRM for general service requests.
The LLM is fine-tuned on 30,000 resolved citizen enquiries from the contact centre, learning the council’s service-specific language, policies, and resolution workflows. When a resident types “My green bin wasn’t emptied on Tuesday and I need a bulky waste collection for an old sofa”, the chatbot handles both issues in a single conversation — checking the collection schedule, logging the missed bin report, and booking the bulky waste collection with available dates.
GPU Requirements
The chatbot must handle peak concurrency during council tax billing season (200+ simultaneous conversations) and maintain sub-2-second response times. A 7B model fine-tuned for council services provides the quality-speed balance needed.
| GPU Model | VRAM | Response Latency | Concurrent Citizens |
|---|---|---|---|
| NVIDIA RTX 5090 | 24 GB | ~0.9 seconds | ~250 |
| NVIDIA RTX 6000 Pro | 48 GB | ~1.1 seconds | ~400 |
| NVIDIA RTX 6000 Pro | 48 GB | ~0.8 seconds | ~450 |
| NVIDIA RTX 6000 Pro 96 GB | 80 GB | ~0.5 seconds | ~700 |
An RTX 5090 handles normal traffic comfortably, with an RTX 6000 Pro providing headroom for billing-season peaks. Private AI hosting ensures all citizen data remains within UK-based, council-controlled infrastructure — non-negotiable for local government.
Recommended Stack
- vLLM serving Mistral 7B fine-tuned on the council’s resolved enquiry history.
- LlamaIndex RAG connecting the chatbot to 800+ council web pages, policies, and service information.
- Function calling integrations with Capita/Civica (council tax), Whitespace/Bartec (waste management), Northgate (housing), and the CRM.
- Authentication layer verifying citizen identity before providing account-specific information (council tax reference + postcode).
- Escalation protocol routing complex or sensitive enquiries (homelessness, safeguarding) to trained officers with conversation context.
For handling phone-based enquiries, add Whisper for voice input transcription. Deploy document AI to process citizen-uploaded evidence (photos of fly-tipping, proof of residency for council tax discount applications).
Cost Analysis
The 18-person contact centre costs approximately £540,000 annually. The chatbot resolving 52% of enquiries (93,600 annually) frees substantial contact centre capacity. The council redeploys freed hours to complex casework and face-to-face services for digitally excluded residents. Eliminating the need for temporary staff during billing season saves an additional £35,000 per year.
The 24/7 availability — a first for the council — means citizens can resolve issues at 10 PM on a Sunday. Resident satisfaction surveys show that service availability is the second-largest driver of dissatisfaction after response times. The council targets a 12-point improvement in its annual resident satisfaction score within the first year of deployment.
Getting Started
Export 30,000 resolved enquiry records from your CRM, categorised by service area and resolution type. Fine-tune the LLM on this dataset. Connect to your council tax system first (the highest-volume enquiry type at 35% of all contacts) and deploy to the council website. Measure resolution rate and citizen satisfaction over 60 days. Add waste management and housing repairs integrations in subsequent phases, expanding the chatbot’s transactional capabilities with each iteration.
GigaGPU provides UK-based dedicated GPU servers for local government chatbot workloads with guaranteed UK data residency, no shared tenancy, and full information governance compliance.
GigaGPU offers dedicated GPU servers in UK data centres with full information governance compliance. Deploy council chatbots on private infrastructure today.
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