◇
AI Strategy & Use-Case Discovery
Find the use cases with real ROI, estimate cost and risk, and build a roadmap leadership can sign off on.
- Opportunity mapping
- Build vs. buy analysis
- Business case & roadmap
AI engineering · Platforms · Sovereign compute · Research
AI solutions that work in sync with every part of your business.
Built around your strategy, data and operations, for measurable results.
Illustrative examples · click a tab
What we do
Four practices, one senior team.
Most AI projects need more than one of these. We cover the full path, so nothing gets lost between strategy, platform, infrastructure and models.
01
AI Engineering
Agents, MCP servers, RAG, copilots, voice and vision, built with evaluation and security from day one.
- Agents & agent infrastructure
- MCP servers & AI gateways
- Fine-tuning & evals
Platforms & Cloud
The heavy lifting: data & AI platforms, landing zones, accelerators and migrations between cloud AI providers.
- Databricks, Snowflake, Fabric, BigQuery
- Azure, AWS & GCP landing zones
- Azure OpenAI ⇄ Bedrock ⇄ Vertex AI
Sovereign GPU Compute
Dedicated, in-region GPU capacity to host, fine-tune and train your own models when public AI clouds are not an option.
- Single-tenant, in your chosen region
- Private hosting of open models
- Training & fine-tuning bursts
Applied AI Research
Custom ML, LLM and speech models that beat general-purpose LLMs on your task, in cost, speed and privacy.
- Distillation & small language models
- Speech recognition & custom voices
- Inference optimisation
Services
Everything between the idea and the SLA.
Pick one focused engagement or combine them. Click any service to see what it covers.
△
AI Solution Architecture
Reference architectures for LLM apps, agents and ML platforms that fit your cloud, data and security constraints.
- Target architecture & ADRs
- Model & vendor selection
- Architecture reviews
○
LLM, RAG & Agent Engineering
Hands-on delivery of copilots, assistants, document intelligence and agentic workflows, with evaluation built in.
- Retrieval & knowledge pipelines
- Tool-using agents
- Eval harnesses & guardrails
□
MLOps & LLMOps Platforms
The plumbing that makes AI boring in the best way: deployment, monitoring, cost control and fast iteration.
- CI/CD for models & prompts
- Observability & tracing
- Inference cost optimisation
◎
AI Governance & Security
Ship responsibly. Practical controls for privacy, safety and compliance, including EU AI Act readiness.
- Risk classification
- Prompt-injection & data-leak testing
- Policies & model documentation
☰
Senior AI Engineers on Demand
Add experienced AI engineers and architects to your team, full-time or part-time, remote or hybrid, B2B-friendly.
- AI / ML engineers
- Data & platform engineers
- Fractional AI architect
From the research lab
Smaller, faster, cheaper. On purpose.
LLM
up to 1000×
lower cost per prediction
Distilling an LLM into a task model 1000× cheaper
Replace a large-LLM API call on a high-volume task (classification, routing, tagging) with a small model trained on the LLM’s own judgements.
100×+ faster: milliseconds, not secondsCPU runs without GPUs
Read the approach →
Voice & speech
30–50%
relative drop in word error rate
Speech recognition for a low-resource language
Fine-tune a Whisper-class model for a language, accent or domain that general models handle poorly, e.g. Azerbaijani, Polish dialects or medical dictation.
real-time streaming on one GPUin-region audio never leaves your jurisdiction
Read the approach →
Inference
2–5×
more throughput per GPU
Inference optimisation for self-hosted LLMs
Serve more users on the same GPUs through quantisation, batching and speculative decoding, without measurable quality loss on your evals.
50–75% lower serving costsame quality on your eval set
Read the approach →
Figures show typical orders of magnitude for each approach compared with calling a large general-purpose LLM. We benchmark on your data before committing to results.
How we work
Start small. Prove value. Scale.
Vendor-neutral
No reseller deals. We recommend what fits: open models, hosted APIs, or no AI at all.
Senior by default
The people you meet in the first call are the people doing the work.
You own everything
Code, prompts, models, evals and docs live in your repositories from day one.
Starting point
Find your starting point in 3 clicks.
Not sure which engagement fits? Answer three short questions and we'll suggest where to begin.
Next step
Let's talk about your AI system.
A free 30-minute call with an Engagement Lead or AI Architect. You'll leave with a clearer view of options, risks and cost, whether or not we work together. Your case doesn't need to fit any box on this site; just tell us what you're facing.
Keep exploring
There’s more to see.
Up next · Services
Everything between the idea and the SLA
Agents, MCP servers, RAG, fine-tuning, voice, vision and governance, 19 hands-on capabilities.
Platforms & Cloud
The heavy lifting behind AI
Data & AI platforms, landing zones, accelerators and migrations between cloud AI providers.
GPU Compute
Your models. Your region. Your GPUs.
Dedicated, in-region GPU capacity to host, fine-tune and train your own models.
Research
Smaller, faster, cheaper. On purpose.
Distillation, small language models, speech recognition and inference optimisation.
Use cases
What this looks like in your industry
24 use cases across finance, healthcare, retail, manufacturing, legal and SaaS.
AIBYOS: AI by OmniSync
AIBYOS is AI by OmniSync Technologies. We build our own work with the same agents, evals and pipelines we ship to clients.