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Model Tuning & LLMOps

Tune It, Ship It, Run It Well

We tune, test, deploy and look after language models that live in your own infrastructure - steady in production, private by default and sensible on cost.

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Model Tuning & LLMOps

Model Tuning

Model Tuning

Model Tuning

Model Tuning

Model Tuning

Model Tuning

Model Tuning

Model Tuning

Model Tuning

Model Tuning

Model Tuning

Inside This Practice

Model Tuning
& LLMOps

Anyone can get a language model to perform in a demo. Keeping it dependable week after week in production is the hard part. We tune models to your tasks and tone, test them against the cases that matter, and ship them with the monitoring, version control, spend tracking and security a live system needs - so your team can run it without anxiety.

Task-Specific Fine-Tuning
Task-Focused
Tuning
Model Evaluation & Benchmarking
Scoring
& Benchmarks
Private Model Deployment
Private
Hosting
Monitoring & Optimisation
Observability
& Optimisation
why choose TokenWave AI
why choose TokenWave AI
Why Choose TokenWave AI

Models That Behave in Production

why-choose
Sharper Results, Smaller Bills

A well-tuned compact model can equal a far larger one on your tasks, for a fraction of the running cost.

why-choose
Steady in Production

Version control, live monitoring and automatic scoring keep every model steady once it is live.

Scope My Project

Host It Anywhere, See Everything

We tune open models such as Llama and Mistral and host them on AWS, Azure, Google Cloud or your own GPU servers.

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integrations
ai
Efficient Tuning

Parameter-efficient methods such as LoRA adapt models to your tasks quickly and without a large compute bill.

Talk It Through
ai
Release Pipelines

Automatic scoring, release, monitoring and one-step rollback for every model version.

Talk It Through

Where It Earns Its Keep

Brand-Aligned Content Generation

On-Brand Content Generation

A model tuned on your approved communications that writes in your brand voice, uses your terminology and follows your editorial rules every time.

  • One voice across every channel
  • Editorial and compliance rules respected
  • Shorter content turnaround
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Intelligent Document Data Extraction

Document Field Extraction

A model tuned to pull specified fields from invoices, forms and reports and return clean, structured data your other systems can use immediately.

  • Output validated against your schema
  • Recognises sector-specific fields
  • Far less manual keying and rework
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Private, Cost-Optimised LLM Deployment

Private, Economical Model Hosting

Moving from a third-party API to a tuned open-source model running in your own environment - tightening data governance and reducing running costs.

  • Lower cost per request at volume
  • Your data never leaves your control
  • Steady, predictable response times
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Our Build Path

How We Tune
& Run Your Models

process
process
process
process
Targets & Baseline

We define the target tasks and measure how current models perform, so improvement is provable.

Data & Tuning

We assemble clean, representative training data and tune the best-suited model.

Evaluation

We score accuracy, safety, speed and cost against the targets you set.

Ship & Operate

We release with monitoring, version control and alerts, and retrain as requirements shift.

6+

Engineering Practices

10+

Sectors We Serve

100%

Built From Scratch, For You

24/7

Agents That Act

Ways to Engage

Choose How We
Work Together

Pilot

/ Pilot

Prove the idea on your own data before you commit to a full build.

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Opportunity-mapping workshop

Working prototype on a data sample

Frank feasibility and payback review

Plan for going live

Recommended

Build

/ Full Build

A hardened, production-grade system connected to your software.

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Design and build from start to finish

Connectors to your apps and records

Evaluation suites and safety limits

Launch, documentation and handover

Scale

/ Run & Improve

Ongoing tuning, monitoring and engineering support as usage grows.

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Monitoring and accuracy tuning

Model and prompt refreshes

New capabilities and use cases

Fast-lane engineering support

FAQ

Questions We Often Hear

Tuning shines when you need a consistent style, structured output or specialised behaviour. For answering from documents that change often, RAG is usually the better fit - and the two work well together.

LLMOps is the discipline of releasing, monitoring, testing, versioning and improving language models in production - the AI equivalent of DevOps.

Often. A compact tuned model can match a large general model on specific tasks at a much lower cost per request.

Yes. We deploy on on-premise GPU servers or private cloud environments and optimise for both speed and cost.
Results in Practice

Related Case Studies

Case studies that show our methods applied to real problems.

Hearing the Customer Clearly
Retail & Customer Experience
Hearing the Customer Clearly

Aspect-by-aspect sentiment and emotion from customer feedback, delivered as dashboards.

Read case study →
Explainable Medical Imaging
Healthcare
Explainable Medical Imaging

Highlights probable conditions in X-rays and scans and shows clinicians the evidence behind each finding.

Read case study →
Network Attacks, Spotted Early
Cybersecurity
Network Attacks, Spotted Early

Tells ordinary traffic from hostile behaviour and alerts security teams immediately.

Read case study →
Browse All Case Studies

Further Reading

Field notes from our engineers on shipping AI that holds up.

All Field Notes
LLMs
21 September 2026 TokenWave AI

General-Purpose vs Sector-Tuned Language Models: Where Each Wins
Automation
7 September 2026 TokenWave AI

Agent Teams: How Specialised AI Agents Run Whole Processes

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