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01
Horienta
Public tenders · Italy
Platform that sends companies the public tenders that fit them every morning, with results and contract data.
AI & Automation
Work that runs on its own
AI systems that take repetitive work off your team: quotes, documents, support and internal search. Built on your own rules, connected to the tools you already use, and running in production.
If a task follows rules, it can be automated. We study how your team works today, find where the hours go, and build systems that do the repetitive part reliably, at any hour of the day.
(a.) What we build
Four kinds of system we build most often.
- (a.)
Automated quoting
Your pricing logic turned into software: thousands of configurations, conditional rules and exceptions, priced in seconds instead of minutes.
- (b.)
Document AI
Delivery notes, invoices, contracts and orders read, classified and checked automatically, then written into your systems.
- (c.)
Process automation
Workflows automated from the first input to the final output, connected to your CRM, ERP, email and spreadsheets.
- (d.)
Assistants and internal search
Assistants that answer from your own documents and data, for your customers or for your team, with sources you can check.
(b.) How we work
How we approach AI.
Your rules first
We start from how your business decides, not from a model. The system follows your prices, your exceptions and your approvals.
In production, not in a demo
We test on your real data and put the system to work inside your processes, with monitoring from the first day.
Measured
Before we start we agree how to measure success: hours saved, response times, error rates. Then we report on them.
(c.) Method
From process to production.
Step 1 of 4
Process analysis
We map the current process: rules, exceptions, volumes and costs, and find where AI makes a real difference.
Step 2 of 4
Technical proposal
Architecture, timeline, costs and success measures, in writing, before any development starts.
Step 3 of 4
Build and test
We build on your business logic and test with your real data until the results match how your team works.
Step 4 of 4
Go-live and monitoring
Gradual rollout, active monitoring and continuous tuning. The system grows with your volumes.
(d.) Related work
AI systems in production.
Just to cite a few, out of the 650+ projects we have handled over the years.
See the full portfolio →
(e.) Questions
What clients ask us.
Do we need clean data before starting?
No. Part of the analysis is understanding the data you have today. We tell you what can be used as it is and what needs work first.
Which AI models do you use?
We choose case by case among Anthropic, OpenAI and Google Gemini models, or open models when data must stay on your own infrastructure.
What happens when the system is not sure?
It asks a person. Uncertain cases go to your team for a decision, and those decisions improve the next ones.
How much is manual work costing you?
Book a free call. We look at your process, estimate what the manual work really costs and show you what can be automated.