Karta AI raises $3 million in seed funding

Karta AI raised $3 million in a seed funding round led by PeerCapital and Cedar Hill Capital.[1] Wyser VC, CDM Capital and Seedstars also participated.[1] The date shown for the announcement is October 22, 2026.[1] Karta AI is a Bengaluru-based voice AI startup founded in 2024 by Vijaypal Singh and Abhishek Kushwaha.[1] The round was led by PeerCapital and Cedar Hill Capital, with Wyser VC, CDM Capital and Seedstars also participating.[1]

Karta AI plans to improve its platform, expand deployments at financial institutions, and strengthen its engineering and go-to-market teams.[1] The company says the investment will also support improvements to end-to-end automation and multilingual capabilities, alongside expansion across financial institutions.[1] Karta AI says the funding will support improvements to its platform, expansion at financial institutions, and stronger engineering and go-to-market teams.[1] For prospective customers, the next useful details to track are how the planned improvements are delivered and which deployments expand.[1]

Karta AI’s platform focuses on inbound customer operations in banking, financial services and insurance.[1] The company says its voice agents manage inbound calls for banks, lenders, fintech companies and insurers.[1] Its platform also supports inbound support, outbound calls and back-office operations for financial services, and delivers customer experiences across voice, chat, WhatsApp and web.[3] Karta AI says its agents can communicate in more than 30 languages.[3] Cedar Hill Capital says the agents integrate with customers’ CRMs, APIs, dialers and ticketing tools.[4]

Karta AI says its Predictive Context Engine enables it to resolve more than 80% of complex L2/L3 inbound cases autonomously.[2] The company also says every call passes policy-guardrail, auditability, human-oversight and access-control checks.[2] Karta AI also says its agents can deliver consistent support around the clock.[6] Cedar Hill Capital says customer call volumes have grown alongside digital adoption, while complex support cases make up a small share of calls but a disproportionate share of support costs.[4] It also says rule-based bots handle simple queries while more complex cases reach human agents.[4]