Rohit-led AI automation service

Pattrn Data services

Business Intelligence Consulting for Professional Services

BI should not be a wall of charts. It should answer the questions leaders keep asking, show where work is stuck, and give AI projects a cleaner base to build from.

Find the drag

Map the process as it actually happens, including handoffs, waiting time, exceptions and duplicated data entry.

Design the guardrails

Decide what can be automated, what needs review, what data is allowed and who owns the output.

Prove the change

Build the smallest useful version, test it against real examples and measure whether it saves time or reduces risk.

Who this service is for

This page is for partners, directors, operations leads and finance teams that need reporting to guide decisions instead of creating another meeting who can see the pressure building. More clients, more admin, more compliance evidence, more systems, and not enough calm time to improve the way work moves through the firm.

Pattrn Data takes a practical route. We look at how your people actually work, where information gets copied, where clients wait, where partners become bottlenecks, and where AI could help without creating new risk.

What the work usually covers

Before tools, prompts or agents, we map the real process and decide what should happen, who owns each step, what data is needed, what should never be automated, and where a person must review the output.

Typical work includes discovery interviews, process mapping, opportunity scoring, supplier and data review, prototype design, implementation support, staff training and governance documentation.

What is safe

  • Start with one named process
  • Keep a human review point for judgement-heavy work
  • Use approved data sources and clear permissions
  • Measure time saved, rework reduced or response time improved

What is not safe

  • Buying tools before mapping the process
  • Putting client data into unapproved AI tools
  • Automating exceptions no one understands yet
  • Treating governance as a policy PDF nobody uses

Useful use cases

Executive dashboards

A practical candidate for scoping, testing and governance before wider rollout.

Operational performance reporting

A practical candidate for scoping, testing and governance before wider rollout.

Client service reporting

A practical candidate for scoping, testing and governance before wider rollout.

Pipeline and capacity reporting

A practical candidate for scoping, testing and governance before wider rollout.

Board packs

A practical candidate for scoping, testing and governance before wider rollout.

BI tool and metric reviews

A practical candidate for scoping, testing and governance before wider rollout.

Questions clients ask

Clear answers before you commit.

What makes BI useful?

Useful BI gives a clear answer to a real decision. If a dashboard does not change what someone does next, it is probably noise.

Which BI tools do you use?

The tool depends on the data and the team. Power BI, Looker Studio, Tableau and lightweight internal reporting can all work if the metric design is sound.

How does BI connect to AI?

BI shows what is happening and where the friction is. That makes it easier to pick automation and AI projects with a business case instead of guessing.