Service 01 · AI & Data

AI development & data analytics, from strategy to production

We design, build and run AI that does real work: generative AI and LLM applications, AI agents, machine learning models and the data platforms underneath them. Our own AI product, Adam, runs in production every day.

Start an AI project See what’s included
  • Since 2014
  • Reply within 1 business day
  • NDA on request
  • English · Italiano · Português

In short

What does Onesight’s AI development service include?

Onesight Global is an AI development company that takes AI from idea to production. We assess AI readiness and pick the use cases that pay off, build generative AI and LLM applications, AI agents and machine learning models, engineer the data pipelines and BI dashboards they depend on, and operate them with monitoring, evaluation and security. Companies in Italy, the EU and Brazil work with us as a turnkey project, a dedicated team or through staff augmentation.

Focus
Generative AI, agents, ML, data and BI
Since
2014
Engagement
Turnkey project, dedicated team or staff augmentation
Languages
English, Italian, Portuguese
Markets
Italy, the EU and Brazil
Response
Within one business day
Confidentiality
NDA on request

Sound familiar?

AI should be paying off by now

  • Pilots that never reach production

    The demo impressed everyone. Months later it still isn’t in front of a customer, and nobody owns the path to production.

  • Data everywhere, answers nowhere

    Spreadsheets, CRMs and databases that don’t agree, and reports that arrive after the decision was made.

  • AI risk nobody owns

    Teams want to use AI; legal wants guarantees on data residency, GDPR and the EU AI Act. Projects stall in between.

  • Too much hype to choose

    Dozens of models, vendors and frameworks, and no reliable way to tell which one will pay off for your business.

What we do

AI and data services, end to end

Six capabilities that cover the whole path, from deciding where AI pays off to running it in production with the data it needs.

  • Strategy

    AI Strategy & Readiness Assessment

    We map where AI creates value in your business, score each use case for impact, feasibility and risk, and give you a roadmap with costs, milestones and the data you need.

    • AI readiness assessment
    • Use-case discovery and prioritisation
    • Build vs buy and model selection
    • Roadmap and business case
  • GenAI · LLM

    Generative AI & LLM Applications

    Assistants, copilots and document intelligence grounded in your own data with retrieval-augmented generation (RAG), so answers are accurate, cited and private.

    • RAG over documents and knowledge bases
    • Chatbots and internal copilots
    • Document extraction and summarisation
    • Fine-tuning and prompt engineering
    • Evaluation suites against hallucination
  • Agents

    AI Agents & Agentic Workflows

    Agents that take actions, not just answer questions: they call your APIs, update your CRM, triage tickets and hand off to people when they should. Adam is one we run ourselves.

    • Tool-using agents with guardrails
    • Human-in-the-loop approvals
    • CRM, ERP and helpdesk integrations
    • Multi-agent orchestration
  • Machine learning

    Machine Learning & Predictive Models

    Forecasting, scoring, recommendation, anomaly detection and computer vision models, trained on your data and measured against a baseline before they ship.

    • Demand and sales forecasting
    • Churn, lead and risk scoring
    • Recommendation engines
    • Anomaly and fraud detection
    • Computer vision and OCR
  • Data engineering

    Data Engineering & Data Platforms

    The pipelines, warehouses and lakehouses that make AI possible: clean, governed, documented data, refreshed on time and ready for analytics and models.

    • ETL / ELT pipelines
    • Data warehouse and lakehouse
    • Data quality and governance
    • Real-time streaming
  • Analytics · BI

    Data Analytics & Business Intelligence

    Descriptive, predictive and prescriptive analytics: dashboards and KPIs leadership trusts, self-service reporting for teams, and analysis that surfaces the signal your competitors miss.

    • KPI design and executive dashboards
    • Self-service BI
    • Predictive and prescriptive analytics
    • Embedded analytics in your product
Start an AI project See our AI in production: Adam, the autonomous sales agent

How we work

From first idea to AI in production

Short iterations with working software at every step, so you decide on evidence instead of slides.

  1. Discover

    We learn the business, audit data and systems, and agree what success means in numbers.

  2. Prototype

    A working prototype on your real data, tested against an evaluation set, so you can decide with evidence.

  3. Build

    Production engineering: integrations, security, access control, evaluation suites and a UI people want to use.

  4. Launch

    Gradual rollout, monitoring of quality, latency and cost per request, and training for your team.

  5. Run & improve

    MLOps and LLMOps: drift detection, retraining, model upgrades and a backlog driven by real usage.

Use cases

Where AI pays off

The use cases we’re asked for most, across industries.

  • Customer service

    Assistants that resolve routine requests around the clock and route the rest to people with the full context.

  • Sales and marketing

    Lead scoring, prospect research, personalised outreach and meeting booking that runs on its own.

  • Operations

    Forecasts for demand, stock and staffing, and anomalies flagged before they cost money.

  • Finance, legal and compliance

    Invoices, contracts and documents read, checked and filed automatically, with an audit trail.

  • Retail and e-commerce

    Recommendations, smarter search and product content generated at catalogue scale.

  • Knowledge work

    One search across internal documents, with answers that cite their sources and respect access rights.

What you get

  • Prioritised AI roadmap and business case
  • Production AI application, integrated with your systems
  • Evaluation suite and quality metrics
  • Data pipelines with documentation
  • Monitoring of quality, latency and cost
  • Handover and training for your team

Technology

Models, frameworks and data tools we work with

Models

  • OpenAI GPT
  • Anthropic Claude
  • Google Gemini
  • Llama
  • Mistral

AI frameworks

  • Python
  • PyTorch
  • scikit-learn
  • Hugging Face
  • LangChain
  • LlamaIndex

Data

  • PostgreSQL
  • pgvector
  • BigQuery
  • Snowflake
  • dbt
  • Apache Airflow
  • Kafka

BI and cloud

  • Power BI
  • Looker Studio
  • Metabase
  • AWS
  • Google Cloud
  • Azure

Why Onesight

One accountable partner, since 2014

  • One accountable partner

    Strategy, engineering, security, automation and design under one roof since 2014, so nothing falls between vendors and one team answers for the result.

  • We run what we build

    Adam, our autonomous sales agent, and WBlow, our EU whistleblowing platform, are our own products in production. Client work gets the same standard.

  • Engineering discipline, everywhere

    Code review, automated tests, security and performance budgets are part of every engagement, not an upsell. What we hand over is documented and maintainable.

  • European contracts, three languages

    EU clients contract with GoLittle (VAT IT13053300961) under Italian law. Our teams work in English, Italian and Portuguese, across Italy, the EU and Brazil.

FAQ

AI & Data: questions, answered

How much does AI development cost?

It depends on scope. A readiness assessment or a proof of concept is a short, fixed-scope engagement; production systems are priced per milestone or as a dedicated team. After a first call we send a written proposal with scope, timeline and cost.

How long does it take to build an AI solution?

A focused proof of concept on your data usually takes a few weeks; a production application usually takes a few months, depending on integrations and compliance. We ship in short iterations, so you see working software throughout.

Can you build AI on our private data without losing control of it?

Yes. We can keep data in your own cloud or in EU regions, use open-weight models you host, enforce the access rights your users already have, and choose API providers whose terms exclude training on your data.

Do you help with GDPR and the EU AI Act?

Yes. We map each use case to its EU AI Act risk category, document data flows for GDPR, and build in the logging, transparency and human oversight the rules ask for. For legal sign-off we work alongside your counsel.

Which AI models do you use?

Whichever fits the job on quality, cost, latency and privacy: commercial models such as GPT, Claude and Gemini, or open-weight models such as Llama and Mistral. We test candidates against your own evaluation set and design so the model can be swapped later.

What is the difference between AI development and data analytics?

Data analytics explains what happened and why, with dashboards and analysis people act on. AI development builds systems that predict, generate or act on their own. Most projects need both, because AI is only as good as the data underneath it, which is why we deliver them together.

Can you add AI to our existing software?

Yes. Most of our AI work extends systems clients already run, such as CRMs, ERPs, helpdesks, e-commerce platforms and internal tools, through their APIs, so teams get AI where they already work.

Do you have AI in production yourselves?

Yes. Adam, our autonomous sales agent, finds prospects, talks to them, books calls and learns from every conversation. It is built with the same engineering practices we bring to client projects.

Put AI to work where it pays off

Tell us about the process or the data you want to improve. We reply within one business day with next steps.

Start an AI project

Or write to hello@onesight.global · call +39 351 9073507