policygaido

Insurance Claims with AI

Founders

Sudhakar Reddy, Chinmay Khasnis

Registration Details

Legal entity: Gaido Insurance Private Limited. CIN: U74900PN2024PTC227093. Registration number: 227093. Incorporated: 9 January 2024. Registrar of Companies: Pune. Country/state of incorporation: India, Maharashtra. Entity type: Private, non-government company. Registered address: S. No. 110/1A, Flat No. 703, Balwantpuram Samrajya, Kothrud, Pune, Maharashtra 411038, India. Authorized share capital: INR 100,000. Paid-up share capital: INR 10,000. Official website identifies the operating entity as Gaido Insurance Pvt Ltd.

Current Revenue

2

Valuation

3.5

Products

GaidoAI: AI-powered health-insurance guidance, policy comparison, coverage-gap analysis, and insurance Q&A., Policy Analyzer: Upload or evaluate policies to identify exclusions, waiting periods, sub-limits, and potential out-of-pocket exposure., fairClaims: Free AI-assisted analysis of rejected, delayed, or under-settled insurance claims, including appeal guidance and document checklists.

Notes

Founded: 2025 per LinkedIn company profile; legal entity incorporated 9 January 2024.
Status: Privately held; operational status indicated by active website and LinkedIn presence. Formal registry status not independently confirmed.
Funding history: No publicly disclosed funding round or investor announcement located.
Funding amount: Not publicly disclosed.
Acquisition: No publicly disclosed acquisition.
Founder LinkedIn: Sudhakar Reddy — https://in.linkedin.com/in/sudhakar-reddy-461a934b; Chinmay Khasnis — https://in.linkedin.com/in/khaschinmay.
Founder backgrounds: Sudhakar Reddy — co-founder, GTM and Product; former Prudential and BCG professional; IIT Madras, IIM Calcutta, CFA Level 1. Chinmay Khasnis — co-founder, Product and Engineering; prior US financial-services product and engineering experience; Harvard Business School entrepreneurship studies and Master's in Computer Science. Founder ages, childhood cities, schooling locations beyond disclosed institutions, and family origins are not publicly disclosed.
Problem statement: Insurance complexity + sales-driven advice + weak claims navigation -> mis-selling, coverage gaps, delayed or under-settled claims, and avoidable financial loss. Alternatives: insurance agents, brokers, insurer portals, comparison marketplaces, consumer forums, lawyers, and manual insurer or regulator escalation.
UNIT METRICS
____________
Metric | Number
Dispute value | 5 INR crore+
Median dispute | 1.1 INR lakh
Active cases | N/D
Setup time | 2 minutes
User price | 0 INR
Claim patterns | 17 types
Reported rating | 4.9 stars
Team size | 2-10 employees
Founded year | 2025
Paid-up capital | 0.01 INR million

Due Diligence Segment
____________________
Market & Sector Thesis: Indian health insurance remains complex, agent-led, and claims-friction-heavy. AI can reduce information asymmetry by translating policy language into personalized guidance and structured escalation workflows.
Market Sizing: Broad opportunity spans India's health-insurance premiums, policyholders, claims-support services, and digital insurance distribution; company-specific TAM is not publicly disclosed.
Operating Traction: Company reports hundreds of active fairClaims cases, more than INR 5 crore of dispute value on-platform, and a median dispute value of INR 1.1 lakh; these are self-reported and unaudited.
Direct Competition: Policybazaar, Ditto Insurance, InsuranceDekho, and Insurance Samadhan in India's digital insurance comparison, advisory, and claims-assistance categories; relative company size is not verified.
MOAT Durability: Potential moat consists of policy-and-claims workflow data, insurer-specific reasoning patterns, regulatory knowledge, and consumer trust in a sensitive category. The moat could be disrupted by insurer-native AI, large comparison platforms, regulatory restrictions, weak claim-outcome performance, or commoditized foundation models.
Plausible probable AI models used: Core model names are not publicly disclosed. Verified technology references include Claude for content scripting, Google Veo for video generation, ElevenLabs for Hindi and regional voiceovers, and an internally built AI pipeline for public-complaint analysis. These references relate to disclosed content or research workflows and do not establish the core production model used by GaidoAI.
Sources: Policygaido homepage — https://policygaido.com/ — page update date not stated; accessed 29 August 2026. Policygaido team page — https://policygaido.com/team — page update date not stated; accessed 29 August 2026. Policygaido terms — https://policygaido.com/terms-of-service — last updated 4 June 2025. Policygaido privacy policy — https://policygaido.com/privacy-policy — last updated 4 June 2025. Gaido AI LinkedIn company page — https://www.linkedin.com/company/gaidoai/ — accessed 29 August 2026. Gaido Insurance registry summary — https://www.zaubacorp.com/GAIDO-INSURANCE-PRIVATE-LIMITED-U74900PN2024PTC227093 — registry information marked as of 13 July 2026. fairClaims website — https://fairclaims.policygaido.com/ — page update date not stated; accessed 29 August 2026. Founder launch post — https://www.linkedin.com/posts/khaschinmay_gaido-ai-health-insurance-advisor-compare-activity-7335653138181332994-ELPr — posted approximately 2025; exact update date not stated in page extract. fairClaims launch post — https://www.linkedin.com/posts/sudhakar-reddy-461a934b_fairclaims-policygaido-gaidoai-activity-7452589504479031296-GZ3F — posted approximately 2026; exact update date not stated in page extract.

Notes from Investor call
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Valuation : 30 crore pre money, so that cap table doesnt get too diluted.
Partnership model : What is ratio of commission: 80(Policy Gaido):20 (Partner)
3 months in the market. Very early seed stage


Metrics

Attribute Metric Reference Company Value
Automation Performance Automation Rate 30% of all claims % -
Automation Performance Document Accuracy 95%+ on validated production fields % -
Claims Outcomes Settlement TAT 30 days days -