Forward deployed AI engineering
Our engineers work alongside your team to build custom AI agents and MCP servers, then run them on large language models hosted in your own data centre. Your data never leaves your network, and every action the AI takes is on the record.
Why AI projects stall
The model is rarely the problem. The hard part is everything around it: your data rules, your systems and the people who have to trust the output. That is the work we do.
Customer records, drawings, pricing and banking data are bound by secrecy rules, PDPA and client contracts. Sending them to a third-party API is not an option.
Useful AI has to read from your ERP, MES, core banking and document stores, and act inside them safely. Off-the-shelf tools stop at the chat window.
Who used the AI, what it saw, what it did and who approved it. Without those answers, risk and compliance teams will say no, and they should.
What we do
We design, build, deploy and support the whole stack, so you are not left stitching together a model vendor, an integrator and a consultant.
FDE
Senior engineers embed with your operations, on site or remote, to learn how the work is really done. They turn that into working software in weeks, not a requirements document in months, and stay until your team is using it.
Agents
Agents that do a defined job: review a loan file, draft a QC report, plan maintenance, answer policy questions with sources. Each one has clear permissions and hands off to a person when it should.
MCP
We build Model Context Protocol servers that give AI controlled, logged access to your systems, such as SAP, MES, SQL databases, SharePoint and internal APIs. Read-only by default, with write access only where you approve it.
LLM
We size the hardware, choose and tune open-weight models, and install the inference stack in your data centre or private cloud. Then we hand it over to your IT team with runbooks, monitoring and support.
Governance
Access control, audit trails, evaluation and approval steps built into the system from the start, and documentation your risk, compliance and audit teams can sign off.
On-premise AI
Everything runs on infrastructure you own or control. Models, prompts, documents, embeddings and logs stay on your network. If your policy requires it, the whole system runs fully air-gapped.
Your network
People & apps
AI agents
MCP servers
Private LLM
AI governance
Governance is part of the design, not a policy document written after launch. Every system we deliver includes these controls.
Single sign-on with your directory. Agents inherit each user's permissions, so AI never becomes a way around your access rules.
Every prompt, retrieved document, tool call and response is logged with the user and time, and stored on your servers.
Actions that change records, send messages or move money wait for a named person to approve them.
Data stays in the country and the building you choose. Nothing is used to train anyone else's model.
Accuracy tests on your own cases before go-live, plus checks for prompt injection and data leakage, repeated when models change.
Documentation mapped to the rules you work under, such as PDPA, BNM RMiT, Hong Kong PDPO and ISO/IEC 27001.
Industries
Manufacturing
Keep drawings, recipes and production data inside the plant while giving engineers and operators an assistant that knows your equipment.
Banking & financial services
Customer information stays within your environment, and every AI-assisted decision is traceable for internal audit and regulators.
Healthcare
Clinical and patient records assistants that keep health data on hospital servers.
Government & GLCs
Sovereign AI for agencies and government-linked companies, with data kept in-country.
Logistics
Agents that read shipping documents, check delivery orders and answer fleet questions.
Energy & utilities
Field inspection reports, asset records and compliance checks for critical infrastructure.
How we work
A typical engagement moves through four stages. We agree scope and success measures at each one, so you can stop or change course between them.
Typically 2 weeks
Our engineers sit with the people doing the work, map the process and data, and pick the one or two use cases with the clearest return.
Typically 4 to 6 weeks
We build a working agent on your real data, in a secure environment, and measure it against the success criteria we agreed.
Typically 4 to 8 weeks
We install the model and agents on your infrastructure, connect them through MCP servers, harden security and train your users.
Ongoing
Your team runs it with our runbooks. We stay available for support, model updates and the next use case.
Our head start
Every business runs on the same building blocks: people, processes, documents and decisions. EMAS, our Enterprise Management Agent System, is a library of agents and MCP connectors for those common operations, tested across our client projects.
Our engineers start your project from EMAS and adapt it to how you work. You get to a working prototype faster, on a foundation that has already been through production.
Try the EMAS demoCarbon reporting with AI
A carbon credit is only worth what can be proven about it. Verificer uses the same engineering we bring to banks and factories to measure, report and evidence carbon, so every tonne claimed can be traced back to its source data.
We prepare greenhouse gas reports and carbon project documentation that follow the Verra Verified Carbon Standard (VCS) and ISO 14064, ready for review by an independent validation and verification body.
Our flagship project
We are developing a carbon project on a forest reserve, where protecting the trees generates carbon credits. AI does the heavy lifting: it compares satellite images over time to watch the canopy, flags possible clearing early, and turns field measurements into biomass and carbon estimates. Our engineers then assemble the evidence into a Verra project document that an auditor can check line by line.
Satellite and drone imagery, field plot data, fuel and electricity records. AI reads invoices, meter data and utility bills so nobody has to retype them.
Calculations follow the chosen Verra methodology or ISO 14064-1 for organisational Scope 1, 2 and 3 inventories, with every emission factor and assumption recorded.
An audit-ready data room for the verification body under ISO 14064-3. Every number in the report opens to the document or dataset behind it.
ISO 14064-1 greenhouse gas inventories for manufacturers and listed companies preparing sustainability disclosures and supply chain reports.
Nature-based project development under Verra VCS, from feasibility and baseline to monitoring reports for each verification period.
Our team holds a patent application in China (No. 202411239529.9) for AI processing of carbon reduction data from electric transport.
Clients & partners
Cloud partners for customers who choose a private cloud instead of their own data centre
About Verificer
Verificer started in 2019 as a software company in Kuala Lumpur and opened in Hong Kong in 2021. Our team of around 20 engineers has built production systems for manufacturers, energy companies, healthcare providers and financial firms.
Today we run two practices built on that engineering: forward deployed AI for regulated enterprises, and AI-assisted carbon reporting for companies and nature projects. Both come down to the same thing, data you can trust and prove.
That background is why we work the way we do. We know that an AI project only succeeds when it is connected to real systems, trusted by the people who use it and accepted by the people who audit it.
Talk to an engineer
Book a one-hour discovery call. You'll speak with an engineer, not a salesperson, and leave with a view on feasibility, hardware and the first use case worth building.
Kuala Lumpur · HQ
No 9, Jalan Dafodil 5/3,+60 12 2828 652 (WhatsApp)
Hong Kong
Unit 9, Flat B, 15/F, Chiap King Industrial Building,+852 6499 6168 (WhatsApp)
Monday to Friday, 9:00 AM to 6:00 PM (GMT+8). Weekends by appointment.
