AI solutions for businesses

Business intelligence, executive dashboards, and analytics as the basis for decisions.

Auditing, cleansing, and validation. Poor data quality is the most common root cause of failed AI projects.

Policies, roles, and processes to manage data as a strategic asset.

A single source of truth for customers, products, and suppliers across the organization.

A unified customer profile built from every channel and touchpoint.

Catch pipeline issues before they affect models or business decisions.

Put data in everyone's hands: each team produces its own insights without waiting on IT.

GDPR + EU AI Act: one integrated compliance roadmap for companies using AI.

Supervised and unsupervised models applied to real, measurable business cases.

Sales and demand forecasts 2–4 weeks ahead. Cuts excess inventory.

Anticipate machine failures with IoT sensors + ML. Eliminate unplanned downtime.

Spot which customers are about to leave before they do. Low-cost retention.

Real-time anomaly detection on transactions, with fewer false positives.

Beyond basic RFM: predictive segments that lift campaign conversion.

Forecasting and anomaly detection on time-based data: sales, energy, and production.

Dynamic pricing based on elasticity, demand, and competition. Better margins without friction.

Visual inspection of 100% of production. Quality control that's faster and more consistent than the human eye.

Extract information from contracts, emails, and unstructured documents.

Track the voice of the customer across reviews, social media, and surveys in real time.

Advanced statistical analytics for risk scoring and decisions in regulated industries.

Neural networks for images, speech, and text when classic models fall short.

SHAP and LIME for auditable models. A must in banking, insurance, and healthcare.

VRP and dynamic routing for fleets and last-mile delivery. Significantly fewer miles driven.

Finite-capacity scheduling with AI. Shorter lead times and better OEE without replacing your ERP.

End-to-end visibility, supplier risk prediction, and multi-echelon inventory optimization.

Flag unusual patterns in operational data, transactions, or sensors before they turn into losses.

Product, content, or service personalization based on each customer's actual behavior.

Automate the full ML lifecycle — feature selection, training, and deployment — in less time.

Smart WMS: dynamic slotting, picking optimization, and automatic replenishment.

Smart telematics, predictive maintenance, and a lower cost per mile.

Computer vision and forecasting to minimize losses in production and distribution.

Lower energy use in industrial plants with ML. We calculate the return from each plant's own consumption data.

Ask your business data questions in plain language. No SQL, no waiting on the data team.

ChatGPT Enterprise and Teams: company-wide rollout with privacy and centralized management.

A 200K-token context window. Analysis of long documents and contracts, and structured writing.

AI built into Google Workspace: Gmail, Docs, Sheets, and Meet with Gemini integrated.

AI analysis of your internal documents. Answers with verifiable citations to your sources.

AI-powered search and research. Cited answers for competitive intelligence and market research.

A coding agent with full access to your repository. It refactors, debugs, and writes tests.

Autonomous code generation from specifications. For larger development tasks.

The AI-native code editor. Whole-project context and edits in plain language.

Midjourney, DALL·E, and Stable Diffusion for marketing, product, and design at a lower cost.

Whisper for automatic transcription of meetings, calls, and training videos.

Synthetic voice for IVR, training, and content. A consistent brand voice across every channel.

LLMs on your own infrastructure. Your data never leaves your network. Ideal for regulated industries.

A visual interface for running LLMs locally. No external APIs. A great fit for non-technical users.

LLMs and ML models on your own hardware. Predictable latency, confidential data, no vendor lock-in.

Open-source AI image generation, fine-tuned on your brand assets. No per-image cost.

Custom eval sets, automated judges, regression detection, and production tracing.

Workflow automation with built-in LLMs. No code for standard processes.

Intelligent OCR and processing of invoices, contracts, and forms. Far less manual typing and checking.

Bots that don't break on exceptions, because AI handles them.

Connect your ERP, CRM, and external APIs to AI capabilities without replacing your current infrastructure.

Demand forecasting, cost alerts, and automation on top of your current ERP data.

Predictive lead scoring, sales forecasting, and automated follow-up on your CRM.

A unified analytics platform for the Microsoft 365 and Azure ecosystem.

A unified lakehouse for data engineering, ML, and analytics at industrial scale.

Data Cloud: scalable analytics with separate compute and storage.

The flexibility of a data lake with the governance of a data warehouse. Delta Lake and Iceberg.

Executive dashboards and self-service analytics for the Microsoft ecosystem.

Advanced visualization for data teams with demanding analytics needs.

Kafka and streaming architectures for decisions made the moment events happen.

Virtual replicas of industrial assets for simulation, optimization, and predictive analytics.

ML inference right on the plant floor or the device, with no cloud dependency.

Production AI that doesn't degrade. Retraining pipelines and model monitoring.

Data lakes, lakehouses, and pipelines designed from day one to feed AI models.

Pinecone, Weaviate, Qdrant: the semantic search infrastructure behind RAG systems.

LLMs and ML models on your own hardware. Predictable latency, confidential data, no vendor lock-in.

Adapt LLMs and ML models to your company's own data and terminology.

A decentralized data architecture for groups with multiple business units.