Case Study · Enterprise AI
How Nocodo LTD cut AI infrastructure costs by 80%
Monthly OpenAI API costs reached $10,000. We deployed a custom on-premises LLM in 4 weeks — bringing costs down to $2,000/month with 3× faster API response times.
80%
Cost reduction
$96K
Annual savings
3×
Faster API responses
4 weeks
Time to deploy
The Challenge
As Nocodo LTD grew, their reliance on OpenAI's API resulted in monthly bills reaching $10,000. Beyond the cost, they faced unpredictable usage spikes and growing concerns about sensitive customer data leaving their infrastructure.
- ✗Unpredictable cost spikes during high-usage periods
- ✗Limited control over API rate limits and performance
- ✗Data privacy concerns with sensitive customer information
- ✗Compliance challenges with data leaving their infrastructure
The Solution
Infrastructure Assessment
Analysed Nocodo's existing server grid and AI workload patterns to identify optimal hardware utilisation.
Custom LLM Deployment
Deployed a customised open-source LLM specifically tuned for Nocodo's use cases, optimised for their server specs.
Performance Optimisation
Implemented intelligent request routing, GPU optimisation, and custom inference pipelines — achieving 3× faster responses.
Compliance & Governance
Set up audit trails, compliance monitoring, and data governance tools to keep all AI operations on-premises.
"LLMDeploy team has unique expertise in understanding our situation and adapting to our needs, while delivering the fastest, reasonable and very affordable winning solutions. As a bonus we received data governance and simplified our compliance efforts."