Industrial manufacturing
Production, quality, maintenance and commercial data rarely explain the same outcome.
Connect the evidence behind yield, rework, downtime, delivery and working-capital decisions.
Enterprise AI for manufacturing and project businesses
Protect the economics of every engineered customer commitment
RightSense helps manufacturing, EPC, valve and pump businesses connect operational evidence to the decisions that protect revenue, margin, delivery and cash.
Prove measurable business value before you scale AI. Start with one economically important problem; our founders lead the evidence, the proof and the decision to scale.
Read-only first Human decision authority Value verified before scale
Where we start
Different industrial models. Different value levers.
The first question is not where to add AI. It is which operating decision is economically important, measurable and narrow enough to prove.
EPC companies
Engineering releases, vendor milestones, change orders and billing drift across project systems.
See schedule, margin and cash exposure early enough for project leaders to intervene.
Valve manufacturers
Engineer-to-order bids depend on specifications, drawings, costing, approvals and certificates.
Reduce quote friction while preserving technical compliance, approval control and bid margin.
Pump manufacturers
Configuration, dealer demand, service history and spares live in separate commercial systems.
Improve configuration decisions, aftermarket visibility and service-led margin without another dashboard.
Two concrete starting points
Use cases with a measurable baseline—not a generic AI promise.
These scenarios show how the value case is structured. The assumptions are illustrative; the diagnostic replaces them with the client's actual volumes, costs, constraints and KPI definitions.
Valve & pump manufacturers
Engineer-to-order RFQ and proposal flow
Specifications, sizing, costing, exceptions and approvals move through email and spreadsheets, slowing the quote while making technical and margin risk hard to see.
Approach: Create one governed RFQ evidence path: extract and cite requirements, reuse only approved engineering content, route deviations to specialists and retain human approval for price, margin and contractual commitments.
Illustrative capacity-value scenario
600 engineered quotes/year × 2 engineer-hours released/quote × ₹1,500 loaded hourly cost
₹18 lakh annual capacity value
Illustration only—not a customer result or forecast. Baseline hours, usable capacity and financial attribution must be validated during the diagnostic.
KPIs to baseline and track
- Median and P90 proposal cycle time
- Engineering review hours per issued proposal
- First-pass technical completeness
- Share of proposals within approved margin policy
WinsProposal supports the governed RFQ workflow; PulseIQ connects proposal decisions to downstream order, margin and delivery outcomes.
Review the full workflowEPC & project manufacturing
Project delivery, margin and cash exposure
Engineering releases, supplier commitments, site milestones, change orders and billing events live in different systems, so a project can look on track after recovery time has already narrowed.
Approach: Use PulseIQ to connect approved project evidence to customer commitments, quantify modeled exposure and route recovery options to the accountable project, commercial and finance owners.
Illustrative value-at-risk scenario
₹25 crore scoped project portfolio × 0.5% avoidable cost or leakage acted on in time
₹12.5 lakh potential protected value
Illustration only—not a promise of savings. Value is recognized only after the action, observed outcome and finance-approved attribution are recorded.
KPIs to baseline and track
- Risk lead time before committed milestone
- Approved change-order cycle time
- Project gross-margin variance at completion
- Milestone billing achieved on the planned date
PulseIQ is the initial operating-intelligence layer for the evidence, decision and value record.
Review the full workflowInitial entry offering
Start with PulseIQ and one measurable management problem.
PulseIQ connects the minimum approved evidence needed to show what is at risk, why it is happening, what action remains possible and how the resulting outcome will be measured.
- One plant, project, product family or order cohort
- Read-only evidence before any integration commitment
- Human approval for commercial and operational decisions
- Modeled value kept separate from verified value
How it works
Diagnose → Redesign → Build → Operate → Verify
One process, a named owner and an agreed measure of value. People, process and technology move together.
01
Diagnose
Trace the current work, quantify the constraint and agree the baseline, data scope and business owner.
02
Redesign
Define the Human + AI workflow, decision rights, exception paths and changes to roles and daily routines.
03
Build
Connect approved evidence, build the smallest useful workflow and test quality, controls and failure handling.
04
Operate
Coach users, run the workflow in the operating rhythm and track adoption, overrides and support needs.
05
Verify
Compare outcomes with the agreed baseline. Finance validates attributable value and the team decides whether to scale.
Why RightSense
Designed for a small, measurable first move.
The initial offer is intentionally narrow: one management problem, the minimum governed evidence and an explicit decision on whether to continue.
Outcomes, not dashboards
Each scope names the revenue, margin, delivery, cash, productivity or risk KPI before the proof begins.
Industrial context
The value model reflects engineered products, project milestones, supplier dependencies and customer commitments—not generic automation volume.
Human decision authority
AI can assemble evidence and prepare options; authorized people retain control of technical, commercial and operational decisions.
Proof-first, right-sized entry
Start with the smallest diagnostic, discovery or platform proof capable of validating measurable value for the priority at hand.
Founder-led initial cohort
RightSense is focusing on five manufacturing clients so senior ownership stays close to discovery, adoption and value verification.
Mohan Babu
Co-Founder & CEO
Founder-led engagement
Your engagement is led by a named founder, with an accountable executive sponsor on your side.
Mohan Babu brings 30+ years of experience across enterprise systems, industrial manufacturing, ERP, PLM, proposal engineering, product configuration, program management, and AI-native transformation. He leads RightSense's platform vision across PulseIQ, WinsProposal, and TalentPulse, focused on measurable outcomes across revenue, margin, productivity, and execution.
RightSense is currently operated as a lean founder-led company, supported by specialist partners and AI-native delivery workflows. This allows us to move fast, keep senior ownership close to customers, and focus every engagement on measurable business outcomes.
- Senior practitioners run every engagement
- No junior teams, no offshore hand-offs
- Measurable business impact with an owner
- Value verified before scale