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One workspace for chat, agents, voice, and data. No stitching tools together, everything already there.
No code. No setup project. ISO 27001 · GDPR.
Type the outcome the way you’d brief a colleague. No configuration, no prompt engineering, no IT ticket.
Alo shows you exactly what it will do before it touches anything. You approve a strategy — never a black box.
The agent works, reports, and keeps running on schedule. The same input gives the same result, every time.
Most enterprise AI dies in the pilot. Alomana ships value before the first status meeting — then scales to the whole company.
Like Claude Code for autonomous operators and Lovable for AI apps, at the organization level. Describe the outcome; Alo builds, validates, and ships a production operator — connected to your live data through a library of connectors — into your workspace.
Chain AI actions into end-to-end workflows in a visual editor. Logged, auditable, and shipped by the people who own the process.
Built-in operators for data analysis, document extraction, and voice, plus industry use cases. Filter by sector and function, then deploy persistent operators into your private workspace.
Alo joins Slack, reads from Microsoft 365, OneDrive, Outlook, Linear, Jira, and Drive — and writes back to your team in plain language. No new tool. No context switch.
Investment banking analysis delivered before the team logs in.
Enterprise sales offers enriched and drafted for every rep.
Vendor onboarding, POs, and audits run end to end.
Round-the-clock monitoring for a $5B+ transaction servicer.
Alomana runs in a dedicated instance inside your environment. Workflows log every input, model call, and output — the audit trail your compliance team has been asking AI for.
Free to start, scale when the work does. See full pricing and plans.
Pick an agent from the AI Store, connect your data, and have it running before lunch. Grow from one workflow to a library.
A private AI workforce across every department — deployed in your cloud, governed by your rules, supported by our team.
Alomana is an enterprise AI operating system where autonomous AI agents — operators — run business processes end-to-end. Describe the work and Alomana builds, validates, and deploys a production operator into a single-tenant private workspace. Model-agnostic including open source, every agent run fully auditable, ISO 27001-certified and GDPR-compliant.
Claude Code and OpenAI Codex give developers an autonomous agent in the terminal. Alomana brings that same agentic power to the whole company — sales, finance, operations — with no code, in a private, ISO 27001-certified instance. It's the secure, org-wide version of the agent your engineers already rely on.
Pre-built agents from the AI Store run the same day. Custom workflows built in the no-code Flow Builder typically go live within 2–4 weeks — no engineering required.
Yes. On enterprise plans, Alomana runs in a dedicated single-tenant instance. Your documents, prompts, and outputs stay inside your instance and never train any model. ISO 27001-certified and GDPR-compliant.
Customers report 80% less time on investment reporting for a European banking client, 5× procurement efficiency for a facilities-management provider, and $1M+ fraud prevented for a $5B+ transaction servicer. Most reach payback in under 90 days.
No. Business users describe outcomes in plain language or build workflows visually in the Flow Builder. Alo designs the interfaces, wires the data, and ships working automations without a line of code.
Yes. Operators run 24/7 on schedules or triggers, and every run is fully logged and auditable — input, output, tools, and user. Exceptions escalate to humans by configurable rules.
Yes. A library of connectors and integrations links operators and AI apps to your databases, data warehouses, CRMs, ERPs, and internal APIs — so what you build runs on live company data inside your own single-tenant environment, not static uploads.
Yes — for AI applications. Describe what you need and Alomana builds it, like Lovable, but the output is a persistent production operator or app — such as a dashboard wired to your database — that lives in a secure single-tenant workspace and runs on live data, not a throwaway prototype.
Yes. Every operator run is logged end-to-end — input, model calls, tool actions, output, and user — so compliance teams can reconstruct exactly what an agent did and why. Fully auditable, with audit data staying inside your instance.
Yes. Operators like Jade (data analysis) and Lens (document extraction) run reporting and monitoring workflows end-to-end, on live data from your systems — a European banking client cut investment-reporting time by 80%. Every run is fully auditable.
Yes. Operators connect to your ERP and procurement systems through the connector library and run supplier monitoring, document processing, and purchase workflows end-to-end — a facilities-management provider reached 5× procurement efficiency.
RPA bots replay scripted steps on structured data and break when inputs change. Alomana operators are goal-driven AI agents: they read context, plan their own steps, act on your systems, and verify results — handling the unstructured documents and exceptions that stop a bot, with every run fully auditable.
New to AI agents? Start with the guides: What are AI agents · What is agentic AI
See Alomana on your own data — a 30-minute walkthrough with your workflows, your documents, your use cases.
