VERIAX orchestrates complete workflows through autonomous AI agents. On-premise deployment for data sovereignty. Model-agnostic architecture for independence from LLM vendors. Native governance for AI Act, GDPR, NIS2 compliance.
I want an analysis on Lombardy: give me a summary with total revenue, top product, best and worst month; generate an interactive chart of monthly revenue split by product category (separate lines, hover with the value); using scikit-learn, train a linear regression on the region's monthly total revenue and forecast the next 6 months (Jan-Jun 2026). Show me R², slope coefficient, and a chart with history + forecast.
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Many organizations process sensitive data that cannot leave their infrastructure. Mainstream SaaS solutions require public cloud connectivity. Private cloud or on-premise deployment removes that constraint, but introduces infrastructure complexity that requires specific expertise.
Enterprise AI platforms require LLM orchestration skills, prompt engineering, vector databases, and infrastructure management. Most organizations do not have these capabilities in-house and cannot afford 6-12 month hiring cycles.
The AI Act requires complete audit trails, configurable human oversight, and lifecycle documentation for AI systems. GDPR and NIS2 add sector-specific requirements. Compliance cannot be an add-on: it must be native to the architecture.
12 monthsvs12 weeks
In-house development
12+ months
VERIAX
12 weeks
THUX Srl has been developing solutions for Finance, Manufacturing, and Public Administration since 1995. VERIAX is not a pivot: it is the natural evolution of a mature engineering framework applied to enterprise LLMs. From the 2019 semantic search prototype to Socratech, Thuxbot, and Subaru document management, each project built capabilities for the next.
Python has been our primary stack since 2005. When LLMs became reliable for critical contexts, we already had the infrastructure and expertise to put them into enterprise production without improvisation.
Certified for quality and information security. VERIAX manages THUX CODE's own quality and security management system - we are our first user. We use it ourselves in production; it is not just a demo.
VERIAX is an orchestration platform for autonomous AI agents. Unlike conversational assistants that answer point requests, VERIAX plans and executes complete end-to-end business processes without continuous supervision.
Four sectors. Four end-to-end orchestrated processes.
Manual policy checks, documentation review, fraud pattern checks, and threshold approvals. Every step requires unstructured human intervention.
The agent verifies policy coverage through SQL, analyzes documents and damage photos, detects fraud patterns in claims history, and applies automatic amount-threshold guardrails with configurable HITL.
Everything you need to build, govern, and evolve your AI agents lives in one platform. Agents, knowledge, governance, and models - ready to use, activatable without writing code.
The tables below compare VERIAX with the two categories of alternatives most frequently evaluated during selection: enterprise conversational AI assistants and cloud AI infrastructure platforms.
Finance team of 10 analysts, 20 hours/month of document production.
Representative scenario. Does not include error reduction, faster decision cycles, or the value of reallocating staff to higher-value activities.
No in-house AI team required. 1 IT Admin + 2-5 domain experts manage the platform after go-live.
The THUX CODE project team is named in the proposal before signature. The same people who analyze your context deliver implementation and user training.
A structured session (2-4 hours) where THUX CODE analyzes your operating context, identifies the fastest-ROI use case, and produces a technical roadmap for first deployment.
Before the session, we run a structured AI Readiness Assessment with your team, so the technical analysis starts from your real context, not from scratch.
2-4 hour session - concrete ROI output
