Umesh Ubriani — Fractional AI Officer for Mid-Market Companies

A note before we begin

Many mid-market companies are making six and seven figure AI decisions today, without a senior AI voice in the room. Some are buying tools that won't survive contact with their data. Others are holding back from moves they should be making.

My work is to be that voice, on retainer, for a few days a month. With a team behind me that can build whatever the strategy calls for.

Umesh Ubriani · 22 years in IT consulting · GE, Infosys, TCS

The advisor

Twenty-two years of large-program judgment, applied to the AI decisions you face this quarter.

I spent the first two decades of my career delivering IT transformation for Fortune 500 clients. First at General Electric, then Infosys, then Tata Consultancy Services. The work spanned sales-force automation, business-process automation, and IT cost optimization.

For the last several years I have led the design and delivery of AI products in production. Document intelligence running at 95% accuracy. NLP-based enterprise automation handling thousands of access tickets a month. AI tender extraction that reduced a sixteen-hour manual process to under ninety minutes.

What I bring to a fractional engagement is the combination. The program-management instinct of someone who has shipped at scale, and the hands-on familiarity of someone still in the work today.

I write regularly about AI for mid-market leaders on LinkedIn.

B.E. Delhi College of Engineering · MBA S.P. Jain

Selected work

Three engagements that illustrate the kind of judgment I bring.

AI tender automationPower-equipment manufacturer
2023

Led the design and delivery of an AI system that extracts engineering specifications from complex tenders. The team I led built it on custom language models, intelligent OCR, and a human-in-loop verification framework. A process that took sixteen to eighteen hours per document now takes about ninety minutes, at 85 to 90% verified accuracy.

SAP access automationGlobal enterprise
2022–24

Designed an ML and NLP-based assistant that allows business users to request and manage SAP access directly, automating a high-volume IT workflow with a full audit trail. The system handles over 1,500 tickets a month across 60,000 users.

AI invoice verificationLive product
Ongoing

Conceptualised and led the build of an AI invoice and freight-verification product that has been running in production with an enterprise client for over a year, at 95% plus accuracy. The product continues to operate and improve under my technical direction.

Client names are kept private out of respect for the relationships. The work, the approach, and the numbers are accurate.

How we'd work

Two ways to engage, designed as a sequence.

Most engagements begin with the first and grow into the second. The intensive is a low-commitment way to see how we work; the retainer is the relationship that compounds.

Engagement · I

AI Strategy Intensive

Two days, on-site, with your leadership team.

A working engagement, not a course. We sit with your data reality, the AI moves already on the table, and the decisions waiting on a senior view. You leave with clarity on the two or three things to do first.

Duration2 days, on-site

FormatWorking sessions with your exec team

ForLeadership teams new to AI, or stuck

Leaves you withA written read-out of where to start

InvestmentDiscussed in our first call

Engagement · II · The destination

Fractional AI Officer

A senior AI presence on call, every month.

An ongoing retainer for leadership teams making AI decisions continuously. The voice in your conversations who has done this before, with a delivery team available when the work needs to flow downstream.

Commitment2 days / month

Minimum term6 months

CadenceWeekly check-ins, monthly review

ForMid-market, 200 to 1,000 staff

InvestmentDiscussed in our first call

What I bring

The work I'm most often asked to do, in plain terms.

AI roadmap and use-case prioritization

Where to start, what to defer, what to stop pursuing. Based on what will actually survive your operational reality.

Build, buy, or partner

The unglamorous decision that quietly determines whether the project ships or stalls. I have made all three calls many times.

Governance and responsible-AI framework

Policies, oversight, and the conversations that need to happen at board level. Written so non-technologists can use them.

Vendor and tool selection

An informed second opinion on what is being pitched to you, and what is missing from the pitch.

Capability-building inside your team

Quietly raising the AI literacy of your existing leaders, so the work outlasts the engagement.

A note on what stands behind this

For enterprise-scale work, my advice flows through a delivery team.

For organizations setting up an AI Center of Excellence at scale, my advisory work flows through PCPL, the firm I founded. Pure advisors give you a deck. With PCPL behind me, the advice is backed by a team that has shipped production AI for over eight years.

visit pcpl.io →

The first conversation

Tell me what AI decision is in front of you. I'll tell you, honestly, whether I'm the right voice to help you make it.

The first conversation is half an hour, on me. We talk about your situation. If it makes sense to work together, we will plan the engagement. If it does not, you will leave the call with a clearer view of what to do next.

Begin a conversation →

or write directly · hello@umeshubriani.com