AI Consulting Services
We get frontier-grade AI running fast and affordable on hardware you already own, because we optimize the models, not just install them.
03 · AI Infrastructure & Deployment
Models tuned and trained to run on your own hardware
We pick the model and the serving engine for the box you own, quantize it and measure it, and when a stock model is not good enough for the job, we train a smaller one on your own data. Your documents, contracts and customer data stay on the premises.
Optimize
We shrink the model so it fits the hardware you have, from a server down to a phone, choose and tune the serving engine for that box, and measure every change before we keep it.
3.0× to 4.3×
faster prompt reading, same model file, same box
We moved the 125B model on our own box to a serving engine built for its chip. When four requests arrive together, the wait dropped from 36 seconds to 12.
Fine-tune
We train an open model on examples of the job done right, taken from your own records.
12 / 12
planted mistakes caught, with 0 false blocks in 30 clean cases
Our 4B review model checks a coding agent's work before the reply goes out. It runs from a 4.3 GB build on a desk-side box, and the weights are public.
Distil
Short on labelled examples? A large model does the job on your real inputs, we check its answers, and a small model learns from them.
4.5 vs 2.2
blind score out of 5 against the stock model, on 40 held-out chats
A 32B model wrote pet chats for our browser game, and a 0.5B model learned from them. It runs in the player's phone browser from a 290 MB download.
Model training for one job you repeat
When your team does the same step hundreds of times a week, a small model trained on your own examples can do it faster and cheaper than a big general one, and it runs on your own server, an edge device or a phone.
Good fits
- Sorting and routing incoming email, tickets or orders
- Pulling the same fields off invoices, forms and delivery orders
- Checking work against your SOP or house rules before it goes out
- Writing replies in your house format and tone
What you get
- A before and after score on a slice of your own data held back from training
- The trained model, which you own, running on your own hardware
- Retraining when your work or your data changes
When we will say no
If the job is answering questions from documents that keep changing, training is the wrong tool: a trained model goes stale and cannot point to its source. We build search over your documents instead, under Enterprise Knowledge AI.
Also in this service
We set the AI up on hardware in your own building, configure it around how your team works and keep it running, so the system is still useful a year after handover. Where a workload genuinely needs cloud, we build hybrid and tell you exactly which parts leave the building.
- On-premises LLM setup, configuration and handover
- RAG pipeline, vector database and knowledge graph build
- Monitoring, updates and retraining after go-live
- GPU selection and cost planning for your own hardware
- Hybrid or cloud only where a workload genuinely requires it
Built and run by us
Tools we built and use every day
Two are free for anyone to use. The third checks our own systems.
Deneb
LiveAnswers whether private AI fits your business and what it costs, from what we have actually done, and hands unusual cases to a person.
- Free, no sign-in
- Terminal agent checks your machine, recommends a model and asks before it fixes anything (open source, MIT)
- Singapore AI box prices read every morning
TokenMark
LiveTracks how fast open models run on AMD Strix Halo, NVIDIA DGX Spark and Apple Mac, so you can check a speed claim before you buy the hardware.
- Free
- Updated every morning, every number linked to its source
- CLI and MCP server for AI agents
Vedis
Not publicOur own security checker. Every morning it scans our public sites for weak settings, exposed files and certificate problems, and alerts us on anything new.
- New tests it drafts wait for a person's review
- Runs on our own systems
Six services
All six services
Number 03, model work on your own hardware, is at the top of this page.
01
Agentic AI Design & Deployment
Agents that do the work, wired into the systems you already run.
- Multi-agent orchestration and routing
- MCP (Model Context Protocol) integration
- Agent lifecycle management and monitoring
- Bounded autonomy architecture design
- Human-in-the-loop escalation workflows
More about agentic AI
We design agents that carry the admin in a workflow end to end: reading what comes in, drafting the reply, updating the record, chasing the follow-up. People keep the judgement calls. Each agent works inside set limits that can be audited, and anything outside them goes to a person. We handle the orchestration, MCP integration and the agent's upkeep from prototype to production.
02
AI Governance, Risk & Compliance
PDPA and EU AI Act mapping, bias audits, and the evidence trail auditors ask for.
- Responsible AI framework development
- Bias auditing and fairness assessments
- Regulatory compliance mapping (PDPA, EU AI Act)
- Audit trail and explainability systems
- AI safety monitoring and incident response
More about governance
Governance is cheaper to build in at the start than to add after launch. We build frameworks that cover bias auditing, regulatory compliance and full audit trails, so your AI systems meet both internal policies and external requirements. Our approach aligns with Singapore's Model AI Governance Framework and global standards. Every deployment includes safety systems, risk registers and continuous monitoring dashboards.
03
AI Infrastructure & Deployment
Models trained or distilled on your own data, then quantized to run fast on your own hardware, benchmarked on the box you will actually use.
- Model optimization, fine-tuning and distillation
- Model training for one job you repeat
- Setup on your own hardware, kept running after handover
04
AI Product Ownership
Someone accountable for the roadmap, the trade-offs and the release.
- Thin-slice PoC delivery (weeks, not months)
- PoC-to-production scaling strategy
- AI-first backlog and sprint management
- Success metrics and ROI measurement
- Stakeholder alignment and change management
More about product ownership
AI products fail when traditional project management is applied unchanged. We bring AI-native product ownership that starts with thin-slice delivery, getting a working PoC into users' hands within weeks. From there, we manage the backlog, define success metrics, and run iterative sprints that de-risk the path to production. We measure the outcomes: adoption, accuracy and return on the spend.
05
Enterprise Knowledge AI
Your documents, searchable and answerable, without shipping them to anyone.
- AI-powered intelligent search and retrieval
- Document Q&A and policy copilot systems
- SharePoint and Confluence AI modernisation
- Content lifecycle governance and curation
- Knowledge graph and semantic layer design
More about knowledge AI
We build search, document Q&A and policy assistants that find the right answer, and show where it came from, in seconds instead of hours. They connect to the systems you already use, such as SharePoint, Confluence and your own data stores. The goal is measurable: fewer support tickets, faster onboarding, and answers your team can check against the source.
06
AI Rescue & Remediation
Broken, stalled or insecure AI projects, taken over and finished.
- AI codebase and architecture audit
- Security review of AI-generated code and pipelines
- Hardening prototypes into production systems
- Adding evals, tests, and human-in-the-loop checks
- Honest go / no-go assessment and remediation roadmap
More about AI rescue
Inherited a half-finished, broken or insecure AI system? Many businesses now run AI that was rushed out, vibe-coded by people who have since left, or built as a demo that never hardened into production: code nobody understands, security holes, no tests, and accuracy that quietly drifted. We audit what you have, fix and secure it, add the tests and human-in-the-loop checks it is missing, and get it production-ready, or tell you honestly to stop.
Thirty minutes, no slides, no obligation
Tell us what is slow, costly or broken, and we will tell you honestly whether we can help.