Services

Build the intelligence. Operate it at scale.

A full-lifecycle AI practice — from models that create value to the operations that keep them reliable — on a foundation of advanced analytics.

Data network visualization
Build

Intelligence that creates business value

We design and deploy AI, ML, and LLM systems that perceive, predict, and prescribe — engineered for production, not the lab.

Artificial Intelligence

Applied intelligence that turns operational data into decisions — built on our patented algorithms.

  • Visual anomaly detection for quality & safety
  • Process optimization & prescriptive engines
  • Computer vision for inspection & yield
  • Embedded copilots & decision support
  • Responsible-AI guardrails & explainability

Machine Learning

Data-driven algorithms customized to the internal and external factors that move your business.

  • Demand, churn & failure prediction
  • Segmentation, clustering & anomaly detection
  • Time-series forecasting engine
  • Feature engineering from internal & external signals
  • Rigorous validation & back-testing

LLM Solutions

Enterprise large-language-model systems grounded in your data and safe to ship.

  • Retrieval-augmented generation (RAG)
  • Domain fine-tuning & prompt engineering
  • Conversational & document-intelligence copilots
  • Agentic workflows across your systems
  • Evaluation, safety guardrails & PII protection

Build · detailed use cases

AI · Steel

Real-time surface-defect detection on the rolling line

Problem

Manual visual inspection can't keep up with line speed, so surface defects slip through — driving scrap and customer rejections.

Approach

A computer-vision model inspects every frame of the rolling line, classifies defect types, and alerts operators instantly — retrained continuously on labeled defect imagery.

Outcome

Defects are caught the moment they form instead of shifts later, cutting scrap and stopping defective coils before they ship.

ML · Cement

Predictive maintenance for kiln & mill equipment

Problem

Unplanned equipment failures halt production and inflate maintenance costs, with no early warning of which asset will fail next.

Approach

ML models trained on sensor streams and maintenance logs predict failures before they occur and rank every asset by risk and time-to-failure.

Outcome

Maintenance shifts from reactive to planned, reducing unplanned downtime and extending equipment life.

LLM · Power

Operations copilot grounded in SOPs & maintenance logs

Problem

During incidents, operators lose critical time searching manuals, SOPs, and historical logs scattered across systems.

Approach

A retrieval-augmented assistant grounded in the plant's own documents returns cited answers, with guardrails that block any ungrounded response.

Outcome

Accurate answers at the point of need and decades of institutional knowledge made instantly searchable.

Operate

The operations that keep AI reliable

Standing up a model is easy; running it at scale is not. We provide the pipelines, observability, and governance to industrialize AI.

MLOps

From model to production — kept healthy, governed, and at scale.

  • Automated training/deployment CI/CD
  • Feature stores & model registries
  • Drift & performance monitoring
  • Automated retraining & champion/challenger
  • Governance, lineage & audit-ready docs

LLMOps

Operationalize generative AI with control, cost-awareness, and confidence.

  • Prompt & model version control
  • Continuous evaluation & regression testing
  • Token-cost, latency & budget guardrails
  • Retrieval & vector-store management
  • Red-teaming & human-feedback loops

AIOps

AI for IT and industrial operations — detect, diagnose, and resolve faster.

  • Anomaly detection across metrics & telemetry
  • Alert correlation & noise reduction
  • Automated root-cause analysis
  • Predictive incident & capacity forecasting
  • IT–OT/IoT data fusion for plants

Operate · detailed use cases

MLOps · Manufacturing

Keeping 440,000 forecasting models healthy

Problem

Hundreds of thousands of demand models drift as conditions change — manual retraining at that scale is impossible.

Approach

Automated CI/CD pipelines monitor drift and retrain on schedule, with a model registry acting as one governed source of truth.

Outcome

Models stay accurate automatically, and every deployment is reproducible, versioned, and audit-ready.

LLMOps · Enterprise

Governing a high-volume assistant's cost & quality

Problem

A production LLM assistant's answer quality and token cost drift unpredictably after every model or prompt update.

Approach

Prompt and model version control with a release gate that blocks any change lowering eval accuracy, plus cost and latency dashboards with budget guardrails.

Outcome

Answer quality is protected on every release and spend stays inside budget — no surprises in production.

AIOps · Power

Cutting alert noise across the IoT sensor network

Problem

Thousands of daily alerts across IT and OT bury the real incidents and exhaust the on-call team.

Approach

Anomaly detection across telemetry correlates related alerts and runs automated root-cause analysis, fusing IT and OT/IoT signals into one view.

Outcome

Thousands of alerts collapse into a handful of actionable incidents, sharply reducing mean-time-to-resolve.

Analytics foundation

The insight-driven core

Our established analytics practice — the bedrock every AI program is built on.

Predictive Modelling

Advanced predictive solutions customized to your needs, using a wide array of external and internal factors and data-driven algorithms.

Interactive Dashboards

Online interactive dashboards with readily available performance metrics in engaging visual formats — agility and speed for your analytics function.

Forecasting

Forecasting for effective campaigns, market-potential mapping, and accurate demand estimation — powered by our proprietary forecasting engine.

Analytics · detailed use cases

Predictive Modelling · QSR

Demand prediction per store, per protein, per day

Problem

Gut-feel demand estimates lead to over- and under-stocking across a fast-growing store network.

Approach

Predictive models forecast demand at store/SKU granularity using external drivers — weather, holidays, and traffic patterns — across 300B+ rows of data.

Outcome

440,000 forecasting models delivering real-time insight and measurably improved speed to service.

Dashboards · Cement

Plant performance at a glance for leadership

Problem

Performance metrics are scattered across systems, leaving leadership without a timely, single view.

Approach

Online interactive dashboards consolidate KPIs into clear visual formats, refreshed continuously for agility and speed.

Outcome

Real-time visibility into operations and faster, data-driven decisions across the plant.

Forecasting · Steel

Demand estimation & market-potential mapping

Problem

Inaccurate demand estimates undermine marketing campaigns and capacity planning.

Approach

Our proprietary forecasting engine produces accurate demand estimates and maps market potential by segment and region.

Outcome

Sharper forecasts feed both commercial strategy and production planning with confidence.

Not sure where to start?

Tell us the business problem. We'll map the right path to value.

Talk to our team