AI workflow automation for complex B2B operations
Your team has the information. It is just scattered across the workflow.
When decisions depend on CRM records, calls, documents, tickets, research, and spreadsheets, important context gets lost. I build AI-assisted workflows that bring the right evidence together, flag what needs attention, and keep the accountable person in control of the decision.
Who I am
A practical AI workflow-product builder for B2B SaaS teams.
I’m Mahadev Upadhyayula—an AI product and workflow builder with 7+ years of experience across product, engineering, data, quality, and operational systems, including PayPal.
Why this work matters
AI should reduce the work your team has to reconcile—not create another answer to verify.
Your team already spends too much time chasing context across systems and people. The important clues are often present, but they are split between CRM records, calls, documents, tickets, spreadsheets, and someone’s memory.
When gaps and contradictions surface late, the cost shows up as rework, delayed handoffs, poor CRM data, slow triage, and decisions made without enough evidence. Generic AI summaries can make that worse because they look complete while concealing missing information and unsupported assumptions.
The work is scattered
You have facts, notes, requests, and signals in different places, with no single reviewable surface for the person who owns the decision.
The risk appears late
Missing owners, conflicting commitments, stale fields, and weak evidence are often discovered after another team has already started work.
The output is hard to trust
A summary is not enough if your team cannot see what was supported, what was inferred, and what still needs review.
A more reliable way to use AI
I let AI prepare the work. Your team decides what moves forward.
I bring the relevant information together
AI prepares a structured view of the facts, sources, and open questions.
I make gaps and conflicts visible early
Rules and checks surface missing information, conflicts, and exceptions before they become downstream problems.
I keep the accountable person in control
A responsible owner can review, approve, return, reject, or escalate the result before anything important changes.
Where I apply this approach
Four workflow areas where incomplete information becomes expensive.
Revenue Intelligence
I prepare account, buyer, CRM, and commercial context before records or revenue decisions move forward. The output is a reviewable change package or account brief your revenue owner can approve, return, or reject.
Implementation Intelligence
I reconcile what was sold, required, and unresolved before delivery begins. The output is a reviewed baseline that makes commitments, gaps, owners, and risks clear.
Quality Intelligence
I turn fragmented escalation evidence into a triage-ready defect candidate. The output helps engineering review what is supported, missing, conflicting, or ready to act on.
Product Evidence
I connect customer, research, usage, and delivery signals before product decisions are made. The output is a source-linked brief rather than an automated roadmap decision.
Selected work
Concrete workflow products, prototypes, and representative evidence.
These projects show how I build useful AI: structured inputs, visible checks, accountable review, and outputs that are safe to act on. Labels make clear whether an example is an independent build, a prototype, or a representative workflow.
Source-backed CRM change package
Independent prototype
CRM Hygiene
I designed this workflow to prepare source-backed CRM change packages for Revenue Operations review before updates are written back.
CRM quality · Evidence review · Human-approved changes
Explore the workflowSold commitment + requirements + open questions
Guided synthetic demo
Sales-to-Implementation Handoff
I built this demo to turn scattered sales commitments, requirements, dependencies, and open questions into a reviewed delivery baseline.
Delivery readiness · Gap detection · Reviewer decision
Explore the workflowMessy request → structured quote rules
Independent demo
iQuote
I built iQuote to convert messy quote requests into structured commercial output with explicit rules and approval gates.
Commercial rules · Structured extraction · Approval gate
Explore the workflowEscalation evidence assembled for review
Representative workflow brief
Quality Intelligence
This workflow prepares escalation evidence for engineering review by making missing context, conflicts, and triage decisions visible.
Support triage · Evidence status · Engineering review
Explore the workflowCustomer signals linked to source evidence
Representative workflow brief
Product Evidence
This workflow turns fragmented customer signals into a source-linked brief before a product decision is made.
Customer evidence · Research synthesis · Product review
Explore the workflowMini-artifacts are concise synthetic UI snippets unless an individual project page states otherwise; they are not client deployments.
Ways to work together
We start with the work that is creating friction now.
Workflow Audit
I clarify the workflow, current pain, available information, decision owner, and whether automation is worth pursuing.
AI Workflow Prototype Sprint
I build and evaluate one focused workflow before we decide whether a wider rollout is justified.
AI Workflow Advisory
I provide ongoing product and technical guidance on priorities, workflow design, measurement, governance, and architecture.
Insights
How I think about making AI useful in real workflows.
Workflow systems
Workflow-first systems
Why bounded workflows matter more than broad autonomy.
Measurement
Beyond AI accuracy
Measure whether outputs support real decisions.
Start with the operating problem
Find the smallest workflow worth making reviewable.
Bring the inputs, current rework, accountable owner, and decision that needs stronger evidence.
Book a Discovery Call