Our approach
How we deliver AI projects: Assess, Pilot, Scale, Support
Short answer
What happens at each stage?
- 1
Assess
We map your current workflows, data and tools, score your AI readiness, and agree where AI can realistically help first.
- Output
- Readiness scorecard and a prioritised roadmap
- Duration
- 2–4 weeks
- 2
Pilot
We take one high-value workflow, build or configure the AI solution, and measure it against how your team works today.
- Output
- A working pilot with measured results
- Duration
- 4–8 weeks
- 3
Scale
We roll the proven workflow out across projects and teams, with training, documentation and an AI usage policy.
- Output
- Rollout plan, training and governance
- Duration
- 2–3 months
- 4
Support
We stay on to monitor results, update tools as models change, and help your team take on the next workflow.
- Output
- Ongoing support as your needs change
- Duration
- Ongoing, monthly
Security & governance
How do you keep our data and AI use safe?
Minimum data
We use only the data a task needs, and remove personal data where the task doesn't require it.
Your systems first
Data stays in systems you control wherever possible. Tools we build run with access controls and logging.
Agreed AI services
We agree in writing which AI services may process your data, and prefer terms that exclude training on it.
Human review
A qualified person checks every AI output before it is issued to a client, authority or site.
Transparency
AI-assisted work is identified internally, so reviewers know what to check and how it was produced.
DPDP Act, 2023
Engagements are planned around your obligations under India's Digital Personal Data Protection Act, 2023.
Read the official text of the Digital Personal Data Protection Act, 2023 (opens in a new tab) on the Ministry of Electronics and Information Technology website. Our training and governance service helps you write your own AI usage policy.
Frequently asked questions
Can we stop after the assessment?
- Yes. Each stage has its own output and is agreed separately. Many firms take the roadmap from the assessment and decide later whether to pilot.
Why pilot before scaling?
- A pilot on live projects shows whether AI actually saves time and how accurate it is in your firm, before you invest in a wider rollout. It also builds trust with the people who will use it.
Who is responsible for AI outputs?
- Your qualified professionals remain responsible for anything issued under your firm's name. Our role is to design workflows where outputs are reviewed and the review is recorded.
Do you sign a confidentiality agreement?
- Yes, we are happy to work under a confidentiality agreement covering your drawings, data and client information.
Talk through your AI plans with an architect
Book a strategy call. We'll look at where AI can save your team time, what it will take, and what to leave alone.