How This Coimbatore SaaS Firm Cracked Hidden Enterprise Prob…

When enterprises compete for lucrative contracts, only a small part of the effort is spent on impressive sales pitches. 

The heavy lifting occurs behind the scenes, involving the careful creation of spreadsheets, the completion of detailed compliance questionnaires, and the assembly of thorough due diligence checklists. 

These disparate efforts converge into a single, critical document: the Request for Proposal (RFP).

Most organisations spend significant time and finances on arriving at the RFP. It requires collecting information across engineering, security, legal, and finance departments.  

This is the very niche on which the trio from Coimbatore — Ganesh Shankar, AJ Sunder, and Sankar Lagudu — based their business.  

Founded in 2015 in Tamil Nadu and now based in Portland, Oregon, Responsive (formerly RFPIO) serves over 2,000 customers and supports more than 20% of Fortune 100 companies. 

How Responsive Uses AI Agents to Manage RFPs

Responsive provides comprehensive, AI-powered solutions for strategic response management (SRM) and issuing RFPs. It assists enterprise clients in centralising their latest information and automating its reuse across RFPs, tenders, bids, and security questionnaires through AI and agentic workflows. 

Recently, the company introduced ‘Agent Studio,’ a no-code platform that allows teams to create custom AI agents for various workflows. These agents offer flexible deployment options, running on demand or according to predetermined schedules, triggering alerts for anomalies, operating in review-first or fully autonomous modes, and maintaining transparent audit trails.

In a conversation with AIM, Ganesh Shankar, CEO of Responsive, shared insights about their latest offerings. Highlighting a use case for Agent Studio, he noted that among a company’s content, some pieces become outdated and irrelevant. “And sometimes it may end up inadvertently getting a proposal with outdated information,” Shankar said.

“You can build an agent within Responsive, constantly looking out for pieces of content that no one has used in the last 365 days. It automatically archives them, ensuring this information is never used in drafting proposals,” he added. 

The company also launched a new TRACE Score to instil confidence in AI-generated content. “TRACE stands for five parameters: Trustworthiness, Relevance, Accuracy, Compliance or Completeness, and Explainability,” explained Shankar.

Each parameter is rated on a scale of 0 to 20, resulting in a total score ranging from 0 to 100. “The higher the score, the greater the confidence. Conversely, if the score is lower, you should double-check or even rewrite the content,” he said, highlighting that TRACE ensures responsive AI content remains reliable, accurate, and free from hallucinations.

The platform’s comprehensive suite, spanning RFP drafting and assessment, organisational knowledge access, branded proposal generation at scale, ad hoc customer inquiry handling, and compliance data consolidation, has delivered measurable results for enterprise clients.

Saving Microsoft 93,000 Hours

Responsive’s solutions have helped companies like Microsoft save 93,000 hours for their sales teams, allowing them to focus on customer relationships and pipeline growth, instead of hunting for content. They have also reduced costs by over $17 million. More than 18,000 sellers can quickly access verified proposal content.

Microsoft’s Proposal Centre of Excellence faced challenges such as fragmented content, increasing bid complexity, and limited automation, which hindered the production of accurate, brand-compliant proposals.

To tackle these issues, Microsoft developed a comprehensive Proposal Resource Library on the Responsive Platform. This library enables AI-driven self-service, automated workflows, and smooth collaboration. Knowledge managers and SMEs keep the content current, while Responsive AI helps by suggesting the most relevant information for proposals and assessments.

Daily Frustration to Market Disruption 

The company’s origins don’t follow the typical romantic startup garage story. Instead, it stems from a daily frustration faced by the founders. 

Shankar, a product manager at an enterprise software firm, was frequently asked to complete various sections of RFPs, a task that fell outside his core responsibilities. 

“When the sales team gets an opportunity through an RFP, it truly takes a village to complete it. It’s never just one salesperson who can handle it alone,” said Shankar. 

Sundar, the company’s CTO, fielded security queries, while Lagudu, the implementation manager, handled deployment and training sections. Pricing remained the purview of the sales team. “So all four parties had to be involved in putting together that one document,” said Shankar. 

This fragmented approach revealed a glaring technology gap. 

“If technologies out there didn’t connect the dots for the 250-employee company that we worked for, we can only imagine how complex it will be for a larger organisation. So that’s when the idea clicked,” said Shankar. 

Notably, even before the ‘GPT’ era transformed the AI landscape, Responsive had embedded substantial machine learning capabilities into its offerings. The platform featured an intelligent recommendation engine that assessed incoming tenders or RFPs, cross-referenced them against historical data, and suggested optimal responses. 

Its auto-response and content-scoring features enabled automatic answer generation, maintaining efficiency and accuracy well before large language models captured mainstream attention.

What’s The Future for Niche Startups?

Despite the proliferation of powerful foundational models, a robust market for specialised RFP software persists. Alongside Responsive, competitors like Loopio, Qvidian, and Conveyer offer varied approaches to response management challenges.

Drawing an analogy with the calculator app on a mobile phone, Shankar said that one may expect it to perform calculations, but to expect it to display weather details or note-taking wouldn’t yield results. “You can add a button to do that, but as a user, that would confuse you.”

He used this to draw a comparison with RFP and proposal software. Just as a calculator must perform its intended function perfectly, an AI platform for RFPs must provide accurate, compliant, and contextually appropriate responses.

General-purpose tools like ChatGPT might answer questions broadly, but they cannot integrate with large enterprise knowledge bases to ensure accuracy, traceability, and regulatory compliance.

Industry experts do believe niche startups still have healthy opportunities despite the rise of powerful foundational models. 

Jeetu Patel, the president and chief product officer at Cisco, said in an interview with AIM: “There will always be opportunities where a startup can find an insertion point — things that a large company might not want to do right away or may not have thought of yet,” said Patel.

“And with AI, I’m waiting for the time when there’s the first single-employee billion-dollar startup,” he added. 

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