Service
Turn your own data into specialised AI
Knowledge integration, fine-tuning and multimodal models, built on your data, governed for regulated work and embedded in the systems you already run.
What we deliver
Specialised AI, built around your data
We connect models to your knowledge, tune them for your tasks and put guardrails around them before they reach production.
Knowledge integration and RAG
Connect models to your documents, records and databases with retrieval-augmented generation, so answers draw on your own knowledge.
Specialised fine-tuning
Tune open models for one task on your data. For a retail promotions model, we fine-tuned Qwen2.5-14B-Instruct on H100 SXM.
Multimodal intelligence
Vision and language models working together, reading images, video and PDFs in one case file, as in our claims proof of concept for Tasco Insurance.
Document AI
Extract data from documents and generate new ones from templates, like the bank loan document extraction we built for a law firm.
Case assessment and reports
An engine assesses medicolegal and insurance cases and generates the report, so clinicians at a leading healthcare group review a draft instead of writing from scratch.
Built into your core systems
The model works where your team works: ERP, CRM, case management and third-party portals, with monitoring and improvement after go-live.
Full stack AI engineering
Three layers in every system we build
Every ALPHV system combines a brain that understands your data, an action layer that does the work, and guardrails that keep it accountable.
The brain
Foundational intelligence core
Models and knowledge that understand your data, from retrieval over your documents to models tuned for one task.
Custom knowledge integration, RAG and beyond
Specialised model fine-tuning
Multimodal intelligence across vision and language
The action
Agentic and autonomous solutions
Agents that act on what the models understand, through the tools, MCP servers and APIs your systems need.
Agentic process automation
Custom tool, MCP and API development for agents
Multi-agent systems
The guardrails
AI governance
Controls that keep every model accountable to your policies and your regulator, including where it runs.
AI safety and alignment
Governance guardrails
Locally hosted models where data must stay in-house
Case note, FPT AI Factory
Train a promotions model on H100 SXM
ALPHV fine-tuned Qwen2.5-14B-Instruct using LoRA with Flash Attention to build a model that recommends promotions from historical sales and promotions data. Access to FPT AI Factory hardware shortens training time and lowers the cost of AI R&D.
Qwen2.5-14B
LoRA
Flash Attention
H100 SXM
Read the case note
Hosting and platforms
Keep sensitive data inside your organisation
Where data must stay in-house, we deploy locally hosted models, for example on your own NVIDIA GPU workstation. Otherwise we choose per project for your data, cost and residency needs.
A law firm’s models run on a locally hosted NVIDIA GPU workstation, so client data stays inside the firm
Fine-tuning on H100 SXM compute through the FPT AI Factory partnership
Cloud deployments on Alibaba Cloud and Google Cloud
Models
Models
Models
Models
Models, YTL AI Labs
H100 compute
GPU workstations
Cloud
Cloud
How we deliver
From business case to a model in production
The engineers who scope your AI are the ones who train, ship and improve it. No hand-offs.
See how we work
01
Discover
Start from the business case
Tech advisory, a data audit and AI strategy research show where a specialised model pays back, and whether your data can support it, before any build starts.
02
Design
Choose models, hosting and guardrails
Retrieval, fine-tuning or both, in the cloud or locally hosted, designed around your existing systems, your data and your regulator.
03
Implement
Build AI into production
Integrate retrieval, fine-tuned models and agents across your core systems, including bank, government and SSM portals.
04
Improve
Improve continuously after go-live
Monitor adoption, review model performance and iterate, with improvement scoped into the build from day one.
FAQ
Questions about AI engineering
How we build, host and govern specialised AI for your business.
Do you fine-tune models or use retrieval?
Both. We connect models to your knowledge with retrieval-augmented generation, and fine-tune specialised models where a task needs it, for example Qwen2.5-14B-Instruct with LoRA on H100 SXM.
Can our data stay in-house?
Which AI models and clouds do you use?
How do we get started?
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Let’s build what’s next
Tell us where your business needs to be. We’ll map the path to get there.