Who it is for
Teams whose local or self-hosted prototype works for one person and falls over for twenty.
The problem it resolves
Slow first tokens, out-of-memory errors at long context, queues under concurrent load, or a GPU bill that does not match the usage.
What we need from you
- Read access to the deployment configuration and logs
- A description of the failing workload and its traffic pattern
- Current hardware, runtime and model versions
What you receive
- Measured baseline under a reproducible load profile
- Root-cause diagnosis covering memory, KV cache, batching, context length, retrieval and infrastructure
- Prioritised remediation plan with expected effect and cost
- Optional implementation of agreed fixes and a re-measurement
Not included
- Rewriting the application
- Guaranteeing a specific improvement before measuring
How the result is accepted
- Before-and-after measurements on the same load profile
- Every change documented and reversible
Commercial structure
From $3,000, typically 1–3 weeks. Excludes hardware, taxes and third-party licences. Final price is fixed in a written scope before work starts.
Dipankar Sarkar · Engagement owner, Neul Labs Limited
One named person is accountable for scope, commitments and acceptance on every engagement, including work delivered with specialist partners.
Typical situations
Inference cost comparison
“Our inference bill is material and growing. Would self-hosting actually be cheaper?”
Production deployment rescue
“Our prototype worked in the demo, but it is slow, unreliable or unsafe with real users.”
Frequently Asked Questions
Our Ollama server is slow with multiple users. Is that a rescue?
Often, yes. Parallel request settings, context length and model choice change memory use and throughput a lot, and sometimes the right fix is a different serving runtime.
Other services
- Private AI Fit Assessment · From $1,500
- Workload Proof Pilot · From $8,000
- Production Deployment · From $20,000
- Managed Private AI · From $750/month
- Partner Deployment Programme · Setup fee, then per-deployment and support charges