Convr: IDP Software Vendor

AI underwriting workbench for commercial P&C insurance with agentic workflow agents achieving straight-through processing and 97% document accuracy.

Overview

Founded in 2016 by underwriters Harish Neelamana and Kuldeep Malik, Convr develops AI-powered solutions for commercial P&C insurance underwriting. The company raised $15-18.2M from investors including Altos Ventures, NFP Ventures, Palm Drive Capital, and Stage 2 Capital.

Convr's strategic direction has sharpened considerably since early 2026. In January, the company launched agentic AI workflow agents for autonomous underwriting decisions, a shift from rule-based automation to proactive AI that operates "much like a digital team member," according to CEO John Stammen. By February, the company added Ohio Mutual Insurance Group (OMIG) as a customer deploying all three core workbench modules to replace what OMIG described as "legacy, siloed tools," a three-module deployment that signals a consolidation play rather than a single-feature pilot.

Enterprise validation has accumulated across multiple relationships. Zurich North America expanded their 2017 partnership across multiple business units after an 8-year relationship, and Lucid Insurance Group achieved straight-through processing with complete automation from submission intake through BindHQ policy administration. Convr's own survey of 200 commercial P&C decision-makers found 83% plan to adopt new AI tools but only 47% currently use technology for underwriting, the adoption gap the platform is positioned to close.

Convr positions itself as the "fourth core system" alongside policy, billing, and claims systems, targeting infrastructure-level adoption with a proprietary data lake containing 85+ million business records and 9+ years of commercial P&C historical data. The company self-reports a 70% reduction in submission-through-quote times; no methodology or third-party validation accompanies that figure.

To support the customer delivery side of this expansion, Convr hired Eli O'Donohue as Head of Data and AI Underwriting Solutions in February 2026. His prior roles at Carpe Data (alternative data scoring), Planck (AI underwriting data), and PCMI (policy and claims administration) span three distinct layers of the commercial insurance data stack, a hiring profile that points toward deeper data integrations rather than incremental document automation improvements.

How Convr Processes Documents

Convr's processing pipeline begins with Intake AI, a patented intelligent document automation layer that ingests, splits, classifies, and prioritizes data from structured and unstructured documents, including ACORDs, loss runs, SOVs, schedules, financial statements, and broker forms, achieving 97% extraction accuracy in approximately 30 seconds versus hours for manual processing. Output is delivered as JSON via a commercial P&C ontology engine developed since 2016, providing a unified data structure for downstream integration with policy systems and rating engines.

Extracted data feeds into Risk 360, which aggregates business insights from thousands of public, private, and customer-preferred data sources alongside the platform's 85+ million business record data lake. As Chris Healey from Zurich North America notes, this "goes far beyond data extraction" to improve "understanding of the true risk profile" through enriched exposure data, surfacing prioritized results in minutes rather than requiring manual research.

Enriched data then enters the agentic workflow layer, where autonomous agents handle referral, declination, financial analysis, and underwriting authority functions using pre-built templates that require no prompt engineering. Field-level confidence scoring enables autonomous decision-making while preserving human-in-the-loop quality control for exceptions. Harish Neelamana describes agents that can "make the referral, drive the declination process, and make corrections on initial clearance and triage" without waiting for commands, the distinction from traditional rule-based automation that Convr frames as its core architectural shift. For a broader view of how autonomous agents are reshaping document workflows across industries, see the agentic document processing capability overview.

The full pipeline supports straight-through processing: Lucid Insurance Group runs complete automation from submission intake through BindHQ policy administration with no manual handoffs, serving as the reference architecture for end-to-end deployment.

Use Cases

Commercial P&C Carriers: Autonomous Underwriting Workflows

Insurance carriers deploy Convr's agentic AI agents to automate underwriting decisions across the submission lifecycle. The agents operate on pre-built templates covering the four primary decision points, referral, declination, financial analysis, and underwriting authority, without requiring custom prompt engineering for each carrier's workflow. Zurich North America's expanded deployment across multiple business units, beginning with automobile lines, illustrates how carriers scale from a single line of business to enterprise-wide adoption.

Specialty Commercial Lines: Replacing Fragmented Tool Stacks

Ohio Mutual Insurance Group deployed all three core modules, Intake, Risk 360, and Convr AI, specifically to consolidate away from "legacy, siloed tools" into a centralized underwriting repository. The competitive frame here is not a single rival product but the fragmented point-solution stacks that commercial lines underwriters typically assemble. Gary Johnson, VP of Commercial Lines at OMIG, cited anticipated gains in "workflow, accuracy, and service" once the platform is operational; quantified benchmarks are not yet disclosed.

MGAs and Insurtech Carriers: Straight-Through Processing

Lucid Insurance Group achieved complete straight-through processing from submission intake through BindHQ policy administration, full automation with no manual handoffs between systems. This deployment serves as Convr's reference architecture for carriers and MGAs targeting end-to-end automation rather than point-solution efficiency gains. Indico Data and SortSpoke address adjacent insurance submission automation use cases and offer a useful comparison point for evaluators assessing the competitive landscape in commercial P&C. Cytora takes a comparable approach to commercial insurance submission digitization and underwriting automation, making it another relevant reference for evaluators comparing purpose-built insurance IDP platforms.

Technical Specifications

Resources

• Website
• Intake AI
• Workbench
• Agentic AI Workflows
• Ohio Mutual Insurance Group Partnership
• Lucid Insurance Group STP Case Study
• AI Adoption Survey

Company Information

Headquarters: Schaumburg, Illinois, United States

Founded: 2016

Founders: Harish Neelamana, Kuldeep Malik

CEO: John Stammen

Head of Data and AI Underwriting Solutions: Eli O'Donohue (hired February 2026; previously Head of Data Strategy at PCMI, Director of Data Solutions at Planck, Senior Director of R&D at Carpe Data)

Funding: $15-18.2M (Altos Ventures, NFP Ventures, Palm Drive Capital, Stage 2 Capital)