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Nimnit Consulting — CRM, Salesforce & Data Science Advisory

Two practices. One integrated firm.

Nimnit Consulting was founded on a simple premise: the companies that win are the ones who can both run their customer platforms with discipline and extract intelligence from their data with precision. Most firms do one or the other. We do both.

Our two practice leads bring a combined 40+ years of enterprise experience — and the rare combination of platform operations expertise and advanced AI capability — to every client engagement.

40+
Combined years experience
2
Specialized practices
B2B & B2C
Enterprise environments
We work at the intersection of systems and intelligence
Your CRM is only as valuable as the data quality and decision-making behind it. Our practices are designed to complement each other — CRM governance creates clean, structured data; data science turns that data into forecasting, automation, and AI-driven insight.
Practitioners, not generalists
Both practice leads have spent their careers doing the work — not just advising on it. Arvind ran enterprise Salesforce governance for 20+ years. Revathy built and deployed ML models at Fortune 500 scale. You get experience that's been tested in production, not just in frameworks.
Fixed-scope engagements. No billable-hour surprises.
Every engagement is scoped, priced, and delivered to a clear outcome. You know what you're getting, what it costs, and when it's done — before we start.

Not sure which practice fits?

Tell us about your situation and we'll point you to the right practice lead — or explore whether a combined engagement makes sense for your business.

We respond within one business day.

Website
CRM Practice — Arvind
arvind011@yahoo.com · (469) 301-4388
Data & AI Practice — Revathy
revathysuran@gmail.com · (469) 655-4595
Location
Prosper, TX · Available remotely worldwide
Who we work with
Mid-market companies (100–2,000 employees) scaling their platforms
Enterprises navigating acquisitions, AI adoption, or data modernization
Retail, CPG, SaaS, media, banking, and hospitality organizations
Leadership teams ready to turn CRM and data into a strategic advantage
CRM & Salesforce Practice

When your CRM needs to work
as hard as you do

Senior Salesforce consulting for mid-market and enterprise companies that have outgrown their CRM setup — or never quite got it right. Governance, security, AI adoption, and the strategic clarity to turn Salesforce into a competitive advantage.

20+
Years Salesforce leadership
5
Salesforce clouds delivered
CEO Award recipient

A practitioner, not a generalist

I'm Arvind Balasubramaniam, an independent Salesforce CRM consultant with 20+ years of enterprise platform leadership. I spent the last decade as a Senior Manager of Business Applications at Rocket Software and Xperi, where I owned Salesforce strategy, governance, security, release management, and AI adoption — across B2B and B2C environments, for Sales, Service, Marketing, Legal, and Advertising teams simultaneously.

I've been the person responsible when CRM breaks at 2am. I've sat in the room when the CRO asks why adoption is still low and the CFO asks why the last Salesforce project ran over budget. That experience is what I bring to every engagement.

  • CEO Excellence Award — Q2 2021, divestiture technology leadership
  • CEO 20/20 Award — Q3 2017, unified customer support portal
  • MS Computer Science, University of Massachusetts Lowell
  • BE Computer Science, Bangalore University
Sales CloudService CloudExperience CloudMarketing CloudSalesforce LightningAgentforceApttus CPQ

"My goal is always the same: leave your CRM in a state your team can own, operate, and grow — without needing me indefinitely."

— Arvind Balasubramaniam

Four ways I work with clients

Every engagement starts with a free 30-minute discovery call to confirm fit and scope.

01
Most requested
CRM Audit & Governance Advisory
A systematic review of your Salesforce org across six domains — security, data integrity, governance, platform health, user adoption, and AI readiness — with a prioritized 90-day remediation plan.
From $4,500 — fixed fee
03
AI Adoption for Salesforce Teams
Hands-on guidance integrating AI into your Salesforce workflows — readiness assessment, tool selection (Agentforce, Einstein, Data Cloud), and an implementation roadmap your team can execute.
$300–$400/hr · or fixed-price project
04
CRM Strategy & 3-Year Roadmap
For organizations at a crossroads — post-acquisition, scaling rapidly, or inheriting technical debt. A clear multi-year CRM strategy, phased roadmap, and governance model to execute it reliably.
$15,000–$25,000 · 4–8 week engagement

From first call to lasting results

Fixed-price engagements designed to deliver clear outcomes, not billable hours.

1
Discovery call
30 minutes to understand your situation and whether we're a fit. Scope, timeline, and fee agreed before anything starts.
30 min · no charge
2
Access & kickoff
Read access to your Salesforce org and documentation. Kickoff call aligns stakeholders and sets the communication cadence.
Days 1–2
3
Discovery & analysis
Systematic review across 58 checkpoints in 6 domains. Stakeholder interviews with your admins, ops team, and business leaders.
Days 3–14
4
Findings & delivery
Written report, prioritized 90-day action plan, and executive readout presentation. 30-day email support window included.
Days 15–20

Start with a conversation

Tell me about your Salesforce situation. I respond within one business day.

Location
Prosper, TX · Available remotely worldwide
Ideal clients
Mid-market B2B SaaS scaling Salesforce without a dedicated CRM leader
Media & advertising firms with complex ad sales CRM needs
PE-backed companies navigating post-acquisition CRM integration
Organizations ready to adopt Agentforce or Einstein AI
Data Science & AI Practice

Turning your data into decisions
that drive revenue

Machine learning, generative AI, and agentic AI advisory for companies ready to move beyond dashboards — into forecasting, automation, and AI systems that operate at enterprise scale. Built on 19+ years of delivery across Retail, CPG, Banking, Insurance, and Hospitality.

19+
Years in Data Science & AI
MIT
Certified Agentic AI
5+
Industry verticals

Enterprise AI built to perform in production

I'm Revathy Suran, a Data Science and AI leader with 19+ years of experience architecting and scaling machine learning, generative AI, and agentic AI solutions that translate advanced analytics into measurable business outcomes. I've built and deployed AI systems at companies like Signet Jewelers and Mindtree, and co-founded an AI analytics consultancy.

I'm an MIT-certified Agentic AI practitioner — actively consulting on the design of autonomous, multi-step AI systems that leverage LLMs, tool-use, and orchestration frameworks to automate complex business workflows. This isn't theoretical. I've built these systems and seen them perform in production at enterprise scale.

My domain experience spans Retail, CPG, Banking & Financial Services, Insurance, and Hospitality — industries where the cost of a wrong forecast or a missed signal is measured in millions.

  • MIT Professional Certificate — Applied Agentic AI for Organizational Transformation, 2026
  • Director of Data Science, Signet Jewelers — AI forecasting across 2,800+ retail locations
  • Co-Founder, Devise Math Solutions — real-time analytics platform for CPG sector
  • MS Statistics, Bangalore University · BS Mathematics, Statistics & Computer Science
PythonRSQLAWSLLMsLSTMProphetARIMAMLOpsComputer Vision
Signature achievement
Enterprise AI Forecasting at Scale
At Signet Jewelers, deployed ARIMA, SARIMA, Prophet, and LSTM forecasting solutions enabling data-driven inventory planning, staffing optimization, and promotional strategy across 2,800+ retail locations.
Computer Vision deployment
100% classification vs. 10% manual baseline
Built and deployed a computer vision AI model on AWS to automatically classify repair images — improving operational throughput while replacing a manual process that achieved only 10% coverage.

"The best AI project isn't the most sophisticated one — it's the one that's still running in production six months later, making decisions your team trusts."

— Revathy Suran

Four ways I work with clients

Every engagement starts with a free 30-minute discovery call to confirm fit and scope.

01
High demand
Agentic AI Strategy & Design
Design autonomous, multi-step AI systems using LLMs, tool-use, and multi-agent orchestration frameworks. From strategy and use-case selection through implementation roadmap — built on MIT-certified agentic AI methodology.
Fixed-price project · scoped on discovery
03
Generative AI & LLM Integration
Practical generative AI strategy for enterprises — use-case identification, model selection, RAG architecture, and integration with existing workflows. Grounded in business outcomes, not AI novelty. Includes governance and responsible AI framework.
Strategy engagement · $10,000–$20,000
04
Analytics Modernization & AI Readiness
For organizations whose analytics infrastructure hasn't kept pace with their ambitions. Data strategy, platform assessment, team capability review, and a prioritized roadmap to AI-ready state — across Retail, CPG, Banking, Insurance, and Hospitality.
$12,000–$22,000 · 4–6 week engagement

Deep domain experience across five verticals

AI models built without domain context fail in production. These are the industries where I've deployed solutions that held up under real business conditions.

RETAIL & CPG

Sales forecasting, inventory optimization, demand modeling, computer vision for operations, and real-time analytics platforms fusing POS, supply chain, and social data.

BANKING & FINANCIAL SERVICES

Predictive models linking satisfaction to financial performance, executive analytics reporting, branch performance forecasting, and data-driven loyalty program design.

HOSPITALITY

Multi-property stay propensity modeling, loyalty program analytics, test-and-control frameworks for offer personalization, and member segment targeting.

E-COMMERCE & SUPPLY CHAIN

Multi-channel e-fulfillment optimization, ship-from-store performance tracking, labor planning dashboards, and supply chain bottleneck analysis using advanced analytics.

B2B TECHNOLOGY & SaaS

Product propensity models, cross-sell recommendation engines, collaborative filtering, upsell model deployment across 15 countries, and automated ML pipelines for real-time decision support.

From use case to production

Every engagement is built around business outcomes first — the AI comes second.

1
Discovery & business alignment
30-minute call to understand the business problem, data landscape, and what "success" looks like in concrete terms. We define the outcome before we discuss the method.
30 min · no charge
2
Data assessment & feasibility
Review of available data, quality, and infrastructure. Honest assessment of what's buildable and what it will take — no overselling of AI capabilities that won't hold in production.
Week 1
3
Model development & validation
Build, test, and validate the model or AI system against business benchmarks. Iterative — with regular checkpoints and stakeholder reviews so nothing is a surprise at delivery.
Weeks 2–6 (varies)
4
Deployment & knowledge transfer
Production deployment with MLOps infrastructure where applicable. Full knowledge transfer to your team — documentation, training, and a support window so the model doesn't become a black box.
Final 1–2 weeks
"
Revathy doesn't just build models — she asks the right business questions first. The forecasting system she delivered reduced our inventory error rate significantly and her team gave us the tools to maintain it ourselves.
Head of Analytics · Retail enterprise client
(reference available on request)

Start with a conversation

Tell me about your data and AI challenge. I respond within one business day.

Location
Prosper, TX · Available remotely worldwide
Ideal clients
Retail and CPG companies with forecasting and inventory challenges
Financial services firms seeking predictive and prescriptive analytics
Organizations ready to deploy Agentic AI or LLM-powered automation
Leadership teams building the case for enterprise AI investment