# Product truth for every technical customer issue.

> Decimal gives support the context engineering uses to debug so teams resolve technical issues faster, with evidence and fewer escalations.

Canonical: https://www.decimal.app/ · Last reviewed: 2026-09-02

## Built for scale, security, and operational clarity

### Works where your team works

Decimal replies inside Plain, Pylon, Zendesk, Jira, Salesforce, GitHub, and Slack, with no new UI or workflow change.

### Evidence, not guesses

Every answer is backed by citations from code, logs, configs, and linked systems.

### Read-only by default

Connect safely to approved sources without write access.

### No training on your data

Your customer data and source code are never used to train foundation models.

### Enterprise security controls

SSO / RBAC / audit logs and encryption end-to-end for governance and reviews.

### Deployment options

Support private storage / VPC or customer-managed components where required.

## What Decimal is

Decimal is an AI support engineer for technical B2B products. It investigates customer issues across code, logs, configurations, production data, documentation, and past tickets, then returns an evidence-backed investigation and a draft response inside the support team's existing workflow.

## Customer evidence

- [Omnea](https://www.decimal.app/blog/omnea-decimal-case-study-2026): 3.8-minute average first response at enterprise scale.
- [Granola](https://www.decimal.app/blog/granola-decimal-case-study-2026): 2× ticket volume handled by the same-size team.
- [Composio](https://www.decimal.app/blog/composio-decimal-case-study-2026): 95% of technical questions deflected in chat.
- [Guide](https://www.decimal.app/blog/guide-decimal-case-study-2026): 0 dedicated support hires needed to scale.
- [Resilinc](https://www.decimal.app/blog/resilinc-decimal-case-study-2026): 62% reduction in mean time to resolution.

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Decimal · Book a demo: https://cal.com/decimal-demo/30m · Markdown index: https://www.decimal.app/llms.txt