Close the capability gap.
Describe the outcome. Antennai reuses what it already has, builds what's missing, tests it and puts it to work.
AI-native business software
Software that builds itself around how you work.
Describe what you need in plain language. Antennai builds it, learns from every correction and fixes itself, inside the rules you set, with a full record of the work.
Defined authority. Checked changes. Full history.Interventional radiology privileges now need 25 supervised cases in the past 12 months.
Requirement updated: draft ready to review
- 14 practitioners hold this privilege
- 3 would fall short at their next review
- Applications already in progress keep the rules they started under
Review changeApply
Your business changes. Your systems should change with it. A new rule, a recurring exception, another spreadsheet to bridge the gap: why wait for your software to catch up?
Antennai builds around your work from shared, tested capabilities. You get the fit of custom software with the economics of shared software, and your organization keeps its own rules and history.
The platform
Ask for what your software can't do yet.
Antennai's AI agents build what's missing, learn from every correction and recover from failures, inside the boundaries you set.
Make corrections count.
Correct something once. Antennai remembers where it 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.
Governance and auditability
AI you can govern. Work you can audit.
Explainable AI with a human in the loop. Set what agents may do, require review where judgment matters, and follow the evidence behind every result.
- Defined authority. Permissions and approval rules set what 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. See the sources, actions, AI involvement and who owns the next step.
Your records and corrections stay with your organization, even when capabilities are shared.
Behind every result
A record you can inspect.
- Evidence
- The sources and rules used
- Authority
- Who acted, and with what permissions
- Change
- The version that ran and its checks
- Actions
- What ran and the outcome
- History
- Earlier attempts and decisions
Each person sees what their role allows.
The context graph
Your context should survive the conversation.
A chat transcript forgets. Antennai's context graph connects the people, rules, evidence, decisions, sources and corrections behind your work, so AI agents act on your context instead of guesswork and you can see what informed every result.
- Ask about your work. Get plain-language answers with the source records behind them.
- Carry corrections forward. Every correction applies wherever it belongs.
- Keep the history. Earlier results keep the rules and evidence used at the time.
Memory in action
Correct it once. It sticks.
A correction should do more than fix the answer in front of you. Antennai remembers where it applies, uses it in every later case and shows who made it.
Earlier decisions stay exactly as they were made, with their original evidence.
October 14 · Reviewer correction
Hours logged at partner job sites count toward Level 2 certification.
November 3 · New application
J. Alvarez, Electrician Level 2: ready for sign-off
- 2,040 of 2,000 hoursIncludes 320 partner-site hours
- Rule appliedCorrection by S. Okafor, Oct 14
Use cases
Different work. A shared foundation.
For work that runs on changing rules, evidence and accountable decisions.
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: assessments, practical evidence, reviewer sign-off and role readiness, built on your competency framework.
Verification against outside sources
Licensing boards, registries and public records, checked at the source and kept as evidence you can show an auditor.
AI and model evaluation
AI governance in practice: test models and AI agents against your requirements, compare them side by side and re-test when they change.
Operational workflows
Intake, review, approvals and case management that change when your process does, with earlier work preserved.
Where does your software fall short?
Bring us the exception, workaround or missing capability that keeps coming back.
Let's explore it →FAQ
Questions, answered
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.
About
Built by people who've done this before
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.
That experience shaped a simple conviction: software should keep adapting as the work changes.
Start with the work
What has your software forced you to work around?
Bring us a workflow that needs to change or a decision you need to defend. We'll show you how Antennai would handle it, the controls it would apply and the record it would keep.
Bring us your hardest workflowOr email info@antennai.com