AI adoption,
agents & compliance
for engineering teams.
VG Tech Consulting helps software companies create agentic system strategies, roll out AI in production, train teams to work with AI agents, and build governance-friendly delivery processes.
Founded by the former Mercer AI Adoption & Engineering Enablement team for APAC. We led AI rollouts across engineering teams and software leadership across the region.
Practical, scalable, and aligned
with how modern teams work.
AI Adoption & Team Enablement
Train teams to use AI tools, copilots, and coding agents effectively.
- Readiness assessment & roadmap
- Hands-on team training and coaching
- Tooling selection and integration
- Pilot design and outcome measurement
Agentic Systems & AI Employees
Define your agentic system strategy and deploy AI agents that work inside your existing workflows.
- Agentic system strategy and roadmap
- Agent architecture and workflow design
- Coding agent rollout for dev teams
- AI employee onboarding frameworks
- Evaluation and monitoring setup
Compliance-Ready AI Operations
Governance from day one, not an afterthought.
- AI governance framework implementation
- SOC 2 and enterprise readiness
- Data handling and access controls
- Audit trail and evidence documentation
A structured approach.
Built from real rollouts.
Special focus on APAC entrepreneurs and regional SMEs. We understand the regulatory landscape, market dynamics, and operational constraints of building and scaling technology companies in the Asia-Pacific region.
The VG Adoption Model
Assess → Prioritise → Design → Enable → Govern → Scale. A repeatable framework built from real rollouts, not theory. Every engagement follows this structure, adapted to your team's constraints.
Engineering-led, not slide-led
Our work is grounded in software architecture, delivery practices, and hands-on implementation. We build alongside your engineers, not above them.
Governance wired in from day one
Audit trails, access controls, and compliance documentation are part of the initial design — not retrofitted after an auditor asks for them.
Outcomes over hours
We scope engagements around results: teams enabled, workflows shipped, compliance passed. You pay for capability delivered, not time spent on-site.
Real engagements.
Proven capability.
Engineering AI Adoption
A software company wanted to adopt AI across engineering in a practical way, but needed the right workflows, training, governance, and rollout model to make it useful and compliant.
- Reviewed engineering processes and delivery patterns
- Created an AI adoption plan for the organization
- Trained engineers to use AI tools effectively
- Supported compliance-oriented process improvements
- Introduced AI-assisted UI workflows using Figma-connected tooling
- Implemented first-pass AI PR reviews with human escalation
- Deployed Claude Code skills for test generation and automation
Within 8 weeks, moved AI usage from ad hoc experimentation to governed operational practice — PR review cycles shortened by ~60%, first compliance audit passed without findings.
HoverBot
The client needed a production-grade AI platform that could support configurable chatbots, knowledge-grounded responses, and safe enterprise-friendly workflows.
- Designed the platform architecture
- Shaped the AI delivery model and team structure
- Defined chatbot and retrieval workflows
- Supported guardrails, knowledge controls, and operational design
- Helped turn the concept into an AI-native product foundation
Production-ready AI platform shipped in 10 weeks. Team independently shipping features within first month post-engagement.
Enterprise AI Platform
A large enterprise needed a secure, governed way for employees to use LLMs internally without exposing sensitive information or relying on uncontrolled public tools.
Designed the architecture for an internal AI platform. Recommended Azure-based private access patterns for LLM usage. Created centralized, controllable employee access. Introduced guardrails to reduce corporate data leakage risk. Connected retrieval systems to SharePoint-based knowledge sources. Enabled AI search across millions of internal documents. Trained employees to use the platform effectively.
Rolled out governed LLM access to 5,000+ employees in 12 weeks with zero data incidents. Internal knowledge retrieval latency dropped from minutes to seconds.
LabCaddy
The client needed a more intelligent way for users to discover science-related products and interact with product information through conversation, not just keyword filtering.
Designed a custom AI conversation flow for scientific use cases. Built an AI-powered search layer for science-related products. Enabled chatbot-driven search and product discovery. Aligned the system around domain-specific language and workflows.
Conversational AI search deployed across the full product catalog — product discovery conversion improved measurably over keyword-only filtering.
A repeatable process.
Built to scale.
Assess Readiness
We map your team's current state: tooling, skills, workflows, and risk tolerance.
Prioritise Use Cases
We identify the 2–3 AI bets most likely to deliver value without overwhelming your teams.
Design Workflows & Controls
Agent workflows, guardrails, and integration patterns are designed together with your engineers.
Train Teams & Launch Pilots
Hands-on enablement. Your engineers learn by building, not by watching slides.
Add Governance & Evidence
Audit trails, access controls, and documentation are wired in before enterprise buyers ask.
Scale What Works
We help you productionise the pilots that proved value and retire what didn't.
A small team.
Senior by default.
VG Tech Consulting is designed around a lean delivery model. Clients work directly with experienced engineers and AI adoption practitioners who can move from strategy to implementation without handoffs and overhead.
This allows us to stay practical, responsive, and high-value while avoiding the bloat of traditional consulting firms.
Our background includes leading AI adoption and engineering transformation initiatives at Mercer across APAC — working with enterprise engineering teams and software leadership across the region.
We've also built AI-native products from the ground up: designing platform architectures, shipping retrieval-augmented systems, and deploying conversational AI into production environments.
We believe the best consulting teams are small, experienced, and hands-on. Clients should work directly with people who understand the technical detail, the operating model, and the practical trade-offs of adopting AI inside real teams.
“Every software team will work with AI agents within two years. The ones that adopt intentionally — with structure, governance, and real enablement — will outperform the ones that don't.”
Content that helps
you decide.
AI adoption checklist before rollout
Twelve questions every CTO should answer before deploying AI tools to engineering teams. Covers tooling, risk, and evidence.
ReadAI coding agents and compliance: how to choose
A practical framework for evaluating AI coding assistants against your data handling, audit, and enterprise requirements.
ReadIndividual vs corporate AI plans: what changes
The shift from personal ChatGPT to a company-wide AI subscription is not just pricing — it's governance, IP, and team trust.
ReadPlanning AI adoption, internal agents, or compliance-ready rollout?
Book a 60-minute AI Adoption Diagnostic. No salespeople, no slides — just a direct conversation about your team, your constraints, and the next right move.
Get our AI Adoption Checklist — 12 questions every CTO should answer before rolling out AI tools to engineering teams.