Decimal AI Raises $4 Million for Customer Support Engineering Platform

Sep 15, 2026
Decimal AI raised $4 million in seed funding and introduced a platform that investigates technical customer issues, performs support actions, and drafts bug fixes for review.
Decimal AI Raises $4 Million for Customer Support Engineering Platform
Image: Decimal AI via PR Newswire

Decimal AI raised $4 million in seed funding and introduced its Customer Engineering Platform, the company announced in a press release. Khosla Ventures and Kearny Jackson led the round, with participation from Atlassian Ventures and Weekend Fund.

The platform's AI Support Engineer answers questions, performs support actions, and investigates code, logs, configurations, production data, documentation, and customer history. It can also create bug fixes for engineering review. Customers include Granola, Resilinc, Tealium, BuildOps, Lucidworks, and a Fortune 5 technology company.

Decimal says the volume of support interactions it resolves has grown 15 fold since the start of 2026, and that Resilinc cut its mean time to resolution from 6.5 days to 2.5 days. The company will use the funding to expand the range of technical issues its system can investigate and deepen integrations with customers' support and engineering tools. It was founded by chief executive Sanjeet Hajarnis and chief technology officer Kevin Raji Cherian.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like AI Funding Brief, Sales & Marketing AI Weekly or Daily AI Brief.

Also, consider following us on social media:

AI Funding News AI Brief AI Brief (X)
Free newsletter

AI Programming Weekly

Weekly news about AI tools for software engineers, AI enabled IDE's and much more.

Guide
AI app builders

AI app builders

Tools that turn a description into a working web or mobile app, and the platforms companies use to build internal tools with AI

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.