# Antennai

> Antennai is an AI-native platform that builds business applications from plain-language direction. AI agents work from a context graph of each organization's people, rules, evidence, decisions, sources and corrections. They build missing capabilities, learn from corrections and recover from failures, within the permissions and checks the organization defines, and every decision keeps its evidence.

## Why Antennai

Your business changes, and your systems should change with it. Off-the-shelf software makes you work its way; custom software fits but is slow and expensive to build and maintain. Antennai builds around your work from shared, tested capabilities, giving you the fit of custom software with the economics of shared software, while your organization keeps its own rules and history.

## What Antennai does

- Close the capability gap: describe the outcome in plain language. Antennai reuses what it already has, builds what's missing, tests it and puts it to work.
- Make corrections count: correct something once. Antennai remembers where the correction applies, uses it in later decisions and shows which correction changed the outcome.
- Recover, then improve: when something fails, Antennai picks up where it stopped, diagnoses the cause from its own records and proposes a tested fix.
- Share the improvement, keep the differences: improvements reach every customer that uses a capability, while each organization keeps its own rules, versions and history.
- Ask about your work: plain-language answers come from the context graph, with the source records behind them.

## Governance and auditability

AI you can govern. Work you can audit. Antennai is explainable AI with a human in the loop.

- Defined authority: permissions and approval rules set what AI agents can do. Models can't override required checks.
- Controlled change: every change is tested before it's adopted, and earlier versions are kept with the record of their use.
- Accountable work: every result records its evidence (sources and rules used), authority (who acted, with what permissions), change (the version that ran and its checks), actions and outcome, and history (earlier attempts and decisions).
- Privacy: each organization's records and corrections stay with that organization, even when capabilities are shared.

## Context graph

A context graph connects the people, rules, evidence, decisions, sources and corrections behind an organization's work, and how they relate. Antennai's AI agents use it to find the right context, apply corrections where they belong and show the records behind every result. Unlike a chat transcript, the context persists: earlier results keep the rules and evidence used at the time.

## Use cases

- Healthcare credentialing and privileging: provider credentialing, medical staff privileging and reappointment, license checks against primary sources, privileges tied to evidence, and re-verification when anything expires.
- Workforce skills and certification: skills-based credentialing and competency management, with assessments, practical evidence, reviewer sign-off and role readiness built on the organization's competency framework.
- Verification against outside sources: licensing boards, registries and public records, checked at the source and kept as evidence for auditors.
- AI and model evaluation: AI governance in practice, testing models and AI agents against an organization's requirements, comparing them side by side and re-testing when they change.
- Operational workflows: intake, review, approvals and case management that change when the process does, with earlier work preserved.

## Frequently asked questions

### What is Antennai?

Antennai is an AI-native platform that builds business applications from plain-language direction. AI agents work from a context graph of your organization: they build missing capabilities, learn from corrections and recover from failures, within the permissions and checks you define. Every decision keeps its evidence.

### What is a context graph?

A context graph connects the people, rules, evidence, decisions, sources and corrections behind your work, and how they relate. Antennai's AI agents use it to find the right context, apply corrections where they belong and show the records behind every result.

### How is Antennai different from workflow automation or no-code tools?

Workflow automation and no-code tools make you design and maintain every screen and rule yourself. With Antennai you describe the outcome. It reuses or builds the capabilities, tests them and puts them to work, then keeps them current as your rules change, with the full history kept.

### Does AI make the decisions in Antennai?

AI agents gather and check evidence, prepare decisions and flag gaps. People approve the decisions that matter. Permissions and required checks set what agents may do, models can't override them, and every step is recorded.

### How does Antennai make AI work auditable?

Every workflow keeps a record of the sources and rules used, who acted and with what authority, which versions ran, where AI was involved and what happened, including earlier attempts. Reviewers and auditors can follow the full trail.

### Can Antennai handle healthcare credentialing and privileging?

Yes. Antennai supports provider credentialing, medical staff privileging and reappointment: requirements built from your bylaws, license checks against primary sources, reviewer workflows and re-verification when credentials expire.

### What happens when our rules change?

Describe the change in plain language. Antennai drafts the new rule, shows who it affects and applies it once approved. Work in progress keeps the rules it started under, and earlier decisions keep their original evidence.

### What should we bring to a first conversation?

Bring one workflow, a requirement that keeps changing or a decision that's hard to defend. We'll show you how Antennai would handle it, what it would build and the record it would keep.

## Company

Antennai was launched in 2022 by the founders of Neuralify, the leading educational technology platform for the intelligent automation market. Neuralify served more than 100 global customers and was acquired by a Nasdaq-listed global technology research and advisory firm.

## Contact

- Website: https://antennai.com/
- Email: info@antennai.com