LLM DEVELOPMENT

Custom LLM Development & Private AI

Choose, adapt and deploy the right large language model for your data, budget and compliance needs - from managed APIs to fully private, on-premise models.

Book a Free AI Consultation How We Deliver

Enterprise-grade security Cloud, private & on-prem Arabic & multilingual 24/7 support

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LLM Development

The right model, not the biggest model

There is no single best LLM. We benchmark frontier APIs and open-weight models on your real tasks, then recommend the combination that meets accuracy, latency, privacy and cost targets - and we engineer the serving, caching and fallback layers that make it dependable.

What We Deliver

Capabilities included in LLM Development

Model selection & benchmarking

Side-by-side tests of GPT, Claude, Gemini, Llama, Mistral and others on your own data.

Fine-tuning (LoRA / PEFT)

Domain adaptation, instruction tuning and preference tuning with curated datasets.

Private & on-prem LLMs

vLLM, Ollama and TGI serving on your GPUs or private cloud with zero data egress.

Small language models

Distilled and quantised models for edge, low-latency and low-cost workloads.

Prompt & context engineering

Prompt libraries, structured outputs, few-shot patterns and prompt versioning.

Inference optimisation

Caching, batching, quantisation and routing to cut token spend and latency.

Technology & Platforms

Tools and models we work with

OpenAIAnthropic ClaudeGoogle GeminiLlamaMistralQwenDeepSeekHugging FacevLLMTGIOllamaLoRAPEFTUnslothNVIDIA GPUsAzure OpenAIAWS Bedrock

How We Deliver

A proven path from idea to production

Define success

Tasks, quality metrics, latency, privacy and budget targets.

Benchmark

Evaluate candidate models on representative data.

Adapt

Prompting, RAG and where justified, fine-tuning.

Serve

Production inference with scaling, caching and fallbacks.

Optimise

Monitor drift, cost and quality; iterate every release.

Use Cases

Where it creates business value

Arabic & regional language AI

Models and prompts tuned for Arabic, Hindi, Tamil, Malay and more.

Confidential data assistants

Private LLMs for legal, finance, defence and healthcare data.

Code & query generation

SQL, DAX and code copilots tuned to your schemas and standards.

Structured extraction

Turn emails, forms and reports into clean JSON for your systems.

Brand-voice content

Consistent tone across marketing, support and sales communications.

On-device AI

Small models for offline and edge scenarios.

Commercials & Engagement Models

Flexible ways to start and scale

Pick the model that fits your stage and risk appetite. Every quote is tailored to your scope - and every cost driver is explained upfront.

FIXED SCOPE

AI Discovery Workshop

1-2 weeks. Use-case discovery, data and architecture review, ROI model and a costed roadmap.

FIXED PRICE

Proof of Concept / Pilot

3-6 weeks. A working solution on your real data with success metrics and a clear go / no-go.

MILESTONE

Fixed-Scope Project

Scoped build with milestone payments, defined deliverables and acceptance criteria.

MONTHLY

Dedicated AI Pod

A cross-functional team - AI engineer, data engineer, solution architect, QA - on a monthly retainer.

SLA

Managed AI Operations

LLMOps monitoring, evaluation, tuning, cost control and incident response under a monthly SLA.

PASS-THROUGH

Usage-Based Costs

LLM tokens, vector databases and GPU compute billed at cost, or run in your own cloud account.

PERFORMANCE

Outcome-Linked Options

For well-measured processes, part of the fee tied to agreed KPIs such as hours saved or cases resolved.

LICENCE

Product & Platform Licences

Subscription for our reusable orchestrator, RAG and MCP accelerators to cut build time.

What drives the price

Scope & number of use cases

Data readiness & quality

Number of integrations (ERP, CRM, APIs)

Model choice & token volume

Cloud, private cloud or on-prem GPUs

Security, privacy & compliance needs

Languages & channels (WhatsApp, voice, web)

Accuracy targets & human review level

Support SLA & hours of coverage

Training & change management

Request a Tailored AI Quote All Engagement Models

FAQ

Frequently asked questions

Should we fine-tune or use an API?

Start with APIs plus RAG and prompting. Fine-tune only when you need consistent format, tone or specialised skill that prompting cannot deliver.

Can LLMs run fully on-premise?

Yes. Open-weight models run on your GPUs with no data leaving your network. We size hardware and handle deployment.

How do you control LLM costs?

Model routing, prompt caching, response caching, batching, smaller models for easy tasks and budget alerts.

Do you support multiple LLM vendors?

Yes. We build a model-agnostic gateway so you can switch providers without rewriting applications.