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From a $10,000 monthly API bill to $2,000 on its own servers.

Nocodo LTD paid OpenAI about $10,000 a month. We moved it to a tuned open-weight model on its own infrastructure, with request routing and GPU tuning, so every AI operation stays in-house.

80%lower monthly cost

Nocodo LTD

Monthly model billBefore / after

~$10,000
~$2,000
Response speed3× faster
Compliance overheaddown ~60%
Difference, per month~$8,000

Reported by the customerThe figures and the quote on this page are Nocodo’s own, as reported to us. We have not published an independent audit of them.

Monthly bill, collapsingIllustrative
Illustration in points: a column of ten amber $1,000 slabs for the $10,000 monthly OpenAI API bill, collapsed to two cyan slabs for about $2,000 on own infrastructure, under a dashed outline of the old height.
OpenAI API · ~$10,000/moown infrastructure · ~$2,000/mo~$8,000/mo difference

Illustrative motion: scroll to collapse the bill. Each slab is $1,000 a month; the two ends are the figures Nocodo reported.

The bill grew with the product.

As Nocodo grew, its reliance on OpenAI’s API pushed the monthly bill to about $10,000. That cost threatened the company’s ability to keep adding AI features for its customers.

  • Cost spikes during high-usage periods.
  • Little control over API rate limits and performance.
  • Privacy concerns around sensitive customer information.
  • Compliance questions whenever data left its infrastructure.

Four steps, on hardware Nocodo already ran.

  1. Infrastructure assessment

    We analysed Nocodo’s existing server grid and AI workload patterns, then mapped a deployment plan that made the most of hardware already in place.

  2. Custom model deployment

    We deployed an open-weight model tuned for Nocodo’s use cases, optimised for its server specifications and configured with caching and load balancing.

  3. Performance tuning

    Request routing, GPU optimisation and custom inference pipelines brought response times down against the cloud baseline.

  4. Compliance and governance

    We set up data-governance tooling, audit trails and compliance monitoring, so all AI operations stay inside Nocodo’s infrastructure.

Four weeks from assessment to go-live.

  1. Week 1

    Infrastructure assessment

    Analysed the existing server grid and AI workload patterns.

  2. Week 2

    Model selection and customisation

    Selected and tuned the model for Nocodo’s use cases.

  3. Week 3

    Deployment and integration

    Deployed the model and integrated it with existing systems.

  4. Week 4

    Optimisation and go-live

    Performance tuning, testing and the production launch.

What changed.

$2,000Monthly cost now, down from about $10,000.

$96,000Saved per year, the difference over twelve months.

3×Faster API responses. Average response went from 50 ms to 15 ms.

~60%Less compliance work, with audit trails and monitoring built in.

100%On-premise. All data stays inside Nocodo’s infrastructure.

In their words.

Transcript · customer quote

“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.”

Almas Abulkhairov, CEO, Nocodo LTD · as reported by the customer

Want the same on your data?

The pilot puts one open-weight model live on your own data in 72 hours, at a fixed $4,900. See every step priced before you decide.