LLM Integration and Fine Tuning in Durban
e10 Infotech provides LLM integration services and fine tuning in Durban, connecting models to your product and cutting cost while raising accuracy.
LLM integration and fine tuning that earns its place in the budget
Connecting a model to a product takes an afternoon. Making it accurate, fast, cheap and stable across model deprecations is the engineering. e10 Infotech Private Limited treats the model as a replaceable component behind an interface you control, so a better or cheaper option can be swapped in without rewriting the product. Fine tuning happens only when prompting, retrieval and routing have been exhausted and the numbers justify it. Businesses in Durban come to us when a model has to run inside a real system rather than a notebook.
What we deliver
- Model selection benchmarked on your own tasks rather than public leaderboards
- Production integration with retries, timeouts, streaming and graceful degradation
- Structured output and tool calling with schema validation on every response
- Prompt engineering under version control, tested like code
- Routing and cascading so cheap models handle what they can and escalate the rest
- Supervised fine tuning and LoRA adapters on open weight models
- Preference tuning and distillation to make a small model match a large one
- Self hosted serving where data residency or volume requires it
How the work runs
Everything starts with an evaluation set built from your real cases, because without it a model change is a matter of opinion. We benchmark candidate models on those cases for accuracy, latency and cost, then integrate the winner behind an internal interface that hides the vendor. Prompts are versioned, diffed and tested in continuous integration. Caching covers repeated context, and routing sends each request to the least expensive model that still passes. Only once that is in place do we look at fine tuning, and then with a clear target: lower cost, tighter formatting or a skill the model cannot be prompted into. Training data is curated and deduplicated against the evaluation set so results are not flattered by leakage.
Where this fits
This work sits inside our AI First Development practice. Private knowledge is supplied by RAG and Knowledge Systems, multi step behaviour by AI Agent Development, and output production by Generative AI Development. Conversational products come from AI Chatbot Development, scheduled processing from AI Workflow Automation, and hosting, tracing and cost control from MLOps and AI Infrastructure. Investment decisions are framed by AI Consulting and Strategy, developer productivity by Building with AI Coding Tools, and the application itself by Software Development.
When fine tuning is the right answer
Fine tuning is worth it when a small model must match a large one to cut cost, when output format must be exact every time, when the task depends on private conventions no prompt can convey, or when latency budgets rule out long instructions. It is the wrong answer for teaching facts, which belongs in retrieval, and for a task nobody has solved with prompting yet. We say so rather than billing for a training run that changes nothing.
Cost, latency and model changes
Cost per request is a design target, held with prompt compression, caching, batching, smaller models and routing. Latency is managed with streaming, parallel calls and speculative execution where it helps. Because hosted models are deprecated on the vendor's schedule, we keep the evaluation set current so a forced migration is a scored comparison run in a day rather than a crisis.
What you get at handover
Source code in your repository, the evaluation set and benchmark results per model, prompt version history, the model interface layer with fallback behaviour, fine tuned weights and training data in your account, tracing dashboards with cost per request, a model migration runbook, and a thirty day warranty on behaviour that does not match the specification.
Working with businesses in Durban
Work for clients in Durban runs remote first: a named engineering team, a scope agreed in writing before anything starts, and demos on a fixed cadence you can hold us to. Working hours overlap your business day and everything is delivered in English.
Data residency rules decide whether a hosted model is usable at all, and they differ by jurisdiction, so we confirm what applies to businesses in Durban before selecting a provider. That answer shapes the architecture rather than following it.
You get one point of contact, senior engineers on delivery, and reporting tied to benchmark results and shipped features rather than activity. Businesses in Durban and the wider region are supported on the same terms.
Ready to get more from your model spend?
Send us the task and your current numbers and we will send a benchmark plan, an approach and a quote.
Serving Durban and the wider region.
Queries raised before signature
Everything worth knowing about LLM Integration and Fine Tuning in Durban.
01Which large language model should we use?
The one that wins on your evaluation set at an acceptable cost and latency. That answer changes every few months, which is why we put the model behind an interface you can swap.
02Do we need fine tuning or better prompting?
Usually better prompting and retrieval first. Fine tuning pays off for cost reduction, exact formatting or private conventions, not for adding knowledge the model can simply be shown.
03How much data do we need to fine tune?
A few hundred high quality, consistent examples often beat tens of thousands of noisy ones. Curation and deduplication matter more than volume for most business tasks.
04What is LoRA and why use it?
It trains a small adapter on top of a frozen open weight model, which makes training cheap, keeps the base model intact and lets you serve several specialisations from one deployment.
05How long does an LLM integration take?
A production integration with evaluation, structured output and monitoring usually takes six to ten weeks. Fine tuning adds two to four weeks depending on data preparation.
06Can you cut our existing model costs?
Often substantially, through caching, prompt compression, routing to smaller models and distillation. We measure current cost per request first so the saving is verifiable.
07What happens when the model we depend on is retired?
The evaluation set is rerun against replacement candidates, the interface layer is repointed and the change ships behind a flag. The work is planned rather than reactive.
08Hosted API or self hosted model?
Hosted is faster to quality and cheaper at low volume. Self hosting wins when data cannot leave your tenancy, volume is high and steady, or a tuned small model matches a large hosted one.
09How do you get reliable structured output?
Schema constrained generation with validation on every response, automatic retry with the validation error fed back, and a fallback path so a malformed response never reaches your database.
10Will fine tuning make the model worse at other things?
It can, which is why we keep a held out general evaluation alongside the task specific one and check both before release. Adapters also let you keep the base model available unchanged.
11Can you run models in our own cloud?
Yes, with vLLM, Ollama or a managed endpoint inside your account, sized against your throughput with autoscaling and cost controls configured before launch.
12How do you measure improvement?
Task accuracy on the evaluation set, plus latency, cost per request and downstream acceptance rate, tracked per release so a regression is visible before customers find it.
13Do you offer LLM Integration and Fine Tuning in Durban?
Yes. e10 Infotech delivers LLM Integration and Fine Tuning for businesses in Durban and the wider region, remote first with a named team and a scope agreed before work starts.
14How do you run LLM projects for clients in Durban?
Working hours overlap the Durban business day, communication is in English, and you get one point of contact with reporting tied to benchmark results and shipped features rather than activity.
Talk to an engineer about LLM Integration and Fine Tuning in Durban.
Four lines is enough to start. You will hear back from someone who does the work, usually the same day, and nothing is sent to a sales desk.
Prefer to set it all out at once? The full brief form asks the longer questions. Or write to [email protected].