Start with the business case
Understand where time, revenue or service quality is being lost. Agree the baseline, the target and the cost of change before choosing the technology.
About RDMI
Technology built around your business.
We help you find where AI can save time and improve everyday work. Then we design and build the software, connect it to your systems and measure how it performs.
Discuss your priorities
Our purpose
Make intelligence useful.
An AI system earns its place when it improves the work around it. That means understanding how enquiries become customers, how information reaches a decision and where a handoff breaks down.
RDMI connects that operating context to the technology. We design agents that work with your existing systems, use the right information and move defined tasks forward within agreed limits.
Our focus is practical: a clear business case, dependable engineering and a way to measure the outcome. We work with your team from the first workflow assessment through adoption and ongoing improvement.
Leadership
Ranjit Rajput
Founder, RDMI
Read Ranjit's perspective on choosing an AI workflow, defining its business case and measuring the outcome.
ValueA defined business case
ContextConnected systems and data
ControlClear operating boundaries
ResultsMeasured against a baseline
Our principles
Principles behind the work.
The decisions that keep an AI investment connected to business performance.
Connect strategy to engineering
Carry the business objective through architecture, integration and the experience of the people who use the system every day.
Make control part of the design
Define what an agent can access, which actions it can take and when a person must decide. Test those boundaries alongside the intended workflow.
Measure what changes
Evaluate completion time, quality, adoption and operating cost. Use the evidence to decide what to improve and where to expand.
Our process
How we work.
A disciplined path from an operating problem to a system your team can use, evaluate and improve.
Explore each stage of the work.
01Understand the work
Map the trigger, the people, the systems and the exceptions. Establish where delays and rework affect the business.
02Define the investment case
Assess potential value against implementation effort, data readiness and risk. Agree the scope, success measures and decision points.
03Engineer and validate
Build the integrations, agent actions and user experience. Evaluate real scenarios, failure paths and human handoffs before release.
04Operate and improve
Introduce the system with clear ownership, monitoring and training. Compare results with the baseline and improve from actual use.
Start with a business priority
Put your next AI investment on a clear business footing.
Bring the workflow, the constraint or the opportunity. We can help define where AI fits, what it would take and how to measure its value.