Description
Alomana is an enterprise AI platform built around autonomous agents that complete work rather than only assist with it. A user describes a desired outcome in plain language to Alo, the platform's agent, which plans the work, gets it approved, and then carries it out across the tools a company already uses.
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The process runs in three stages. First, Alo turns a described outcome into a proposed plan, such as connecting CRM and enrichment sources, scoring accounts, and drafting offers, for a person to approve before anything runs. Second, Alo builds and executes the work itself, including apps, workflows, voice lines, and Slack answers, showing its reasoning at each step so a person can follow along or step in. Third, deployed agents keep running on a schedule or in response to events, and the library of agents a company builds is shared across teams.
Alomana can build and deploy persistent internal apps from a plain-language description, connecting to a company's live data through a library of connectors. It supports multiple frontier models, including Claude 4.5 Sonnet, GPT-5, Gemini 2.5 Pro, and Llama 4, so a task can be matched to a specific model. Every run is logged, including inputs, outputs, tools used, and the user involved, for later review. The platform runs in a dedicated, single-tenant instance with EU data residency in Frankfurt, AES-256 encryption at rest, and TLS 1.3, and it reports ISO 27001 and GDPR compliance; customer data is not used to train models.
Alomana's AI Store offers prebuilt agents for common workflows, including investment reporting, transaction monitoring for fraud, tailored sales offers, inbound voice intake, procurement automation, and invoice reconciliation. The company cites deployments at a large European facility-services provider handling procurement, compliance, and operations across 60-plus countries, a major esports event organiser running event operations, player data, and broadcast workflows, and a European pharmaceutical company using it for regulatory document processing and clinical coordination.
Agents can be reached from Slack, email, or a phone line, so a team asks for work in tools it already uses. Alomana is aimed at enterprises automating operations such as procurement, compliance, and reporting, with a demo run on the prospect's own data and use cases; pricing is not published and is arranged through a sales conversation.
- CategoryAI Agent Builders
- Pricing ModelContact sales
- DeploymentCloud
- PlatformsWeb
Alomana's Core Features
Plain-language task requests that Alo turns into a proposed, human-approved plan before it runs
Agents that build and run apps, workflows, voice lines, and Slack answers across a company's stack
Scheduled and event-triggered agents that keep running after the first setup
A shared library of deployed agents that teams across the company can reuse
Support for multiple frontier models (Claude 4.5 Sonnet, GPT-5, Gemini 2.5 Pro, Llama 4) selectable per task
Full audit logging of every run's inputs, outputs, tools, and user
Dedicated single-tenant deployment with EU (Frankfurt) data residency and no model training on customer data
Prebuilt AI Store agents for reporting, fraud monitoring, sales offers, voice intake, procurement, and invoicing
Access through Slack, email, or a phone line in addition to the web platform
How to use Alomana?
Describe an outcome: Tell Alo what result you want in plain language, with no configuration.
Review the plan: Approve or edit the step-by-step plan Alo proposes before it runs.
Let Alo execute: The agent builds the app or workflow and carries out the work, showing its reasoning.
Connect your data: Link CRMs, spreadsheets, and other systems through Alomana's connectors.
Reuse and schedule: Save agents to your team's library and set them to run on a schedule or trigger.
Audit the runs: Check the logged input, output, and tools for any run when you need to verify it.
Alomana's Use Cases
- Procurement automation
- Investment and finance reporting
- Fraud and transaction monitoring
- Sales offer generation
