Products

Bring AI into your business processes.

A management application for your business, a backoffice for your teams or an assistant connected to your systems. We adapt our products to your processes, reducing initial development work and leaving room to grow.

Adaptive Data Agent

AI that adapts to your work.

ADA connects AI to your data and processes. Already have business software? We connect it. Need a tailored app? We build it with ADA’s modules. Find information and update records in the app, through WhatsApp, Telegram and email, or from Claude and ChatGPT through a connector.

Explore ADA ada.aton-tech.it

Professionals and small businesses

Start with what you need.

Spreadsheets, paper, documents or an existing app: we start with what you have. We organise your data and make it accessible through WhatsApp too. If you need business software, we build it around you, starting with the features that matter.

Enterprise

Query your data and manage your processes.

We connect ADA to existing databases and generate the backoffice from the data model. Chatbots and connectors bring AI into your tools for complex analysis and operations. With architecture for large volumes, private AI options, permissions and audit configured for your project.

AI PLATFORM

AI Platform

The platform we use across enterprise engagements to integrate AI into real workflows: automations, RAG over corporate documents, high-performance data transformation pipelines. It is designed to be tailored to each client context and integrated with existing systems.

Capabilities

Multi-format ingestion and RAG over corporate knowledge bases (documents, ERP, databases, business systems)
Multi-model orchestration with routing by cost, latency and quality
Parallel data processing for large-volume conversions, with performance tested against the project’s workload
End-to-end process automation: extraction, classification, normalization, validation
Full observability: tracing, quality score, cost-per-request, feedback loop
Native integration with existing systems, with no forced rewrites and no parallel platforms

In action

1 / 3

RAG pipeline

Hybrid retrieval over corporate documents, with source citations

2 / 3

Excel → ERP conversion

Map-reduce AI pipeline: heterogeneous supplier files into the ERP format

3 / 3

AI Copilot

Embedded assistant over corporate data: search, summarize, take action

Use case

RETAIL · TAKEOFF

Client

TakeOff: multi-supplier Excel conversion for large-scale retail

Context

TakeOff receives Excel files daily from hundreds of suppliers, each with its own format, layout and conventions. Conversion to the unified format of the internal ERP required hours of manual work per file, with frequent errors and limited scalability. The volume of data processed every day made any sequential approach impractical.

What we did

AI conversion pipeline that recognizes schema and semantics of each input supplier format
High-performance computing map-reduce architecture: each file is split into chunks processed in parallel by AI models
Optimization algorithms to minimize model calls and maximize throughput
Automatic validation of the output file against the ERP format, with anomaly flags
Direct integration into the client's ERP

Outcome

hours → seconds
time per converted file: adaptable prompts
across Excel formats, most suppliers covered: ERP ingestion
client reference data from the source system

CONVERSATIONAL AGENTS

Conversational Agents

Conversational agents for complex business activities: first- and second-line customer support with access to internal systems, financial support for corporate asset allocation, IT operations on complex infrastructures. They are connected to the client's data and processes, operate within defined permissions and escalate when needed.

Capabilities

First- and second-line customer support: reduction of recurring requests and resolution of complex cases with direct access to internal systems, structured escalation to a human operator when needed
Internal financial assistant: portfolio analysis, asset-allocation recommendations, scenario simulations, support for treasury and cash management
Conversational IT operations: configuration, provisioning and monitoring of complex systems through natural language, with runtime validation and full audit trail
Orchestrated execution: agents act on corporate systems, not just suggest. Domain guardrails, safe rollback, granular authorizations
Corporate knowledge search: users find in seconds what would otherwise require long manual searches, with citations and links to internal sources
Long-term contextual memory, native multilingual, integration with existing systems with no rewrite

In action

1 / 3

Smart Customer Care

First- and second-line support with access to systems and customer history

2 / 3

Financial assistant

Internal support for asset allocation, market scenarios and treasury decisions

3 / 3

IT Operations

Configuration and control of complex systems via conversational agent, with validation and audit

Use case

FINTECH · IT OPERATIONS

Client

Configuration and control of multi-tenant systems during client onboarding

Context

Logifuture operates a complex multi-tenant platform: every new client requires provisioning and configuration across multiple internal systems (wallet, KYC, payment gateways, product configurations), with cross-system dependencies and domain-specific rules. Onboarding operations were concentrated in a small group of technical teams, with bottlenecks, manual errors, unpredictable timelines and limited visibility on each client status.

What we did

Conversational agent connected to internal provisioning, configuration and monitoring systems
Business language → technical operations: the agent translates high-level requests into API calls toward the right systems, in the right order
Runtime validation of every configuration against domain rules, with safe rollback on error or conflict
Native audit trail: every operation tracked, authorized and reversible. Compliance without overhead
Orchestrated execution: the agent acts, validates and reports state, not just suggests
Structured escalation: when operations leave known patterns, they're passed to the specialized team with the full session context

Outcome

days → minutes
average client onboarding time: multi-system ops
in a single conversational session: native audit trail
every action tracked and reversible

How to start

Want to see how it fits your case?

Tell us how you work, which tools you use and what you want to improve. We will propose a starting point with a clear scope, timeline and cost.