AI adoption,
agents & compliance
for engineering teams.

VG Tech Consulting helps software companies adopt AI across engineering teams. The firm provides structured rollouts of AI tools (coding agents, LLM assistants), designs and deploys AI agent workflows, and implements compliance-ready AI governance frameworks. Based in Singapore, serving companies across APAC.

A 60-minute session to pressure-test your AI adoption approach. The review covers current state (tooling, workflows, governance) and identifies the two or three gaps most worth closing first. No salespeople, no slides. You leave with a short written summary of where things stand and what would happen first.

Engagements come in four shapes. A Diagnostic is a focused 60-minute review with a written follow-up. A Hands-on Demo is a 60-90 minute walk-through of an agentic SDLC setup in a real repository, with no commitment required. A Sprint is a 2-8 week hands-on engagement to design and ship specific workflows or governance. An Embedded Retainer puts a dedicated senior consultant alongside one or two of your engineers under your engineering leadership, on monthly time-and-materials, typically in a 12-month shape, with a standard baseline of around 35 hours per week.

Every engagement is led end-to-end by a senior partner. The person you scope with is the person you ship with, across the full contract. No delivery-management layer, no rotating bench. Delivery capacity is amplified the same way clients are advised to amplify theirs: with AI agents running inside a guardrailed SDLC (the same agentic patterns installed for clients), and a vetted specialist network selectively brought in when an engagement benefits from extra bandwidth on a specific problem. Clients always work with, and are accountable to, the senior partner.

Yes. A 60-90 minute hands-on demonstration of an agentic SDLC workflow is available, from branch protection through AI code review and autonomous agents, walked through in a real repository. It is the fastest way to see whether the approach fits your team. No commitment, no slides.

You do. All work product created during the engagement (tools, code, documentation, configurations, prompt libraries, and custom integrations) belongs to the client. The standard contract assigns IP to the client on delivery. No residual rights are retained over client-specific work.

During assessment, developer time is capped at around 1-2 hours per person per week. A single point of contact on the client side coordinates deliverables, and structured onboarding is prepared upfront so context is not repeated across sessions. All tool and process changes go through a small-group proof of concept before team-wide rollout.

Tool-agnostic, with no vendor affiliations. Engagements span the modern AI tooling landscape, including OpenAI, Anthropic (Claude), Azure AI / Azure OpenAI, AWS Bedrock, GitHub Copilot, Cursor, Claude Code, Codex, LangChain, RAG pipelines, Azure DevOps and GitHub Actions automation, and MCP integrations. The default is to work within your existing stack and reuse tools the team already knows, so the learning curve stays low. A different tool is recommended only where it meaningfully improves the outcome, with the team supported through the transition.

Mutual NDAs are standard on every engagement, and enterprise engagements are under NDA, so client names are not disclosed publicly. Case studies on this site are either fully named (with written permission) or anonymised to a descriptor level that reveals nothing about the client beyond industry shape and scale. Client code, data, prompts, and configurations are never shared outside the engaged team without explicit written permission. During evaluation, four options are available: (1) anonymised reference calls with past clients under mutual NDA, (2) named reference conversations with the founders of HoverBot and LabCaddy who have publicly consented, (3) professional references for the partners via LinkedIn, and (4) a 60-90 minute hands-on demonstration of the practice in action.

Based in Singapore, serving companies across APAC — from Series-A startups to global firms with 5,000+ employees. The founding team led AI adoption and engineering enablement programmes at Mercer across the region, with deep familiarity in the operational, regulatory, and market dynamics of scaling technology organisations in Asia-Pacific.