AI and analytics are no longer optional — they are essential to staying competitive.

We help organizations unlock value by transforming raw data into strategic foresight, optimizing decisions at every level of the enterprise. From demand forecasting and AI use case design to decision dashboards and data governance, we tailor solutions that are practical, scalable, and integrated into real operations. Whether you’re at the beginning of your AI journey or ready to refine advanced systems, we offer the technical and strategic expertise to guide your next step with confidence.

Our Engagement Approach:

• Research & Innovation: Forecastability study, data audit, and use-case selection with PoV experiments; target architecture & governance; ROI-backed roadmap.
• Execution & Delivery: Build data pipelines, models, and dashboards; MLOps and adoption plan tied to business KPIs.
• Rescue & Support: Model drift & data-quality recovery, dashboard adoption boost, SLA-based monitoring and enhancement sprints.

A solid AI strategy turns hype into results. We help organizations assess readiness, design scalable use cases, and decide whether to build or buy. With a balanced lens on technology, ROI, and organizational maturity, we guide leadership teams in making clear, future-proof AI investment decisions.

• AI maturity and readiness assessment: We evaluate your current capabilities, systems, and talent to determine how ready you are for adopting AI solutions.
• Identification of high-impact use cases: We map business pain points and match them to AI opportunities, ensuring your efforts focus on areas with measurable impact.
• Build-or-buy advisory (internal vs vendor solutions): We help you decide whether to develop AI tools internally or select the right external vendor, based on cost, timeline, and fit.
• Pilot project design and vendor management: We design structured pilot initiatives and manage third-party AI vendors to ensure alignment, performance, and measurable results.

Engagement Example:
R&I — maturity & portfolio, build-vs-buy analysis → Execution — stand up the first pilot(s) with governance → Rescue — vendor/solution review and reset.

Reliable AI and analytics begin with structured, trustworthy data. We help you design future-proof data architectures, enable responsible access, and ensure your data flows support both operations and insight. Our governance approach balances control with agility — allowing teams to innovate without compromising quality or compliance.

• Structuring data flows across departments and systems: We define scalable data architectures that unify data silos and enable efficient sharing across functions and platforms.
• Data governance frameworks (ownership, access, quality control): We implement governance models that define who owns what data, who can access it, and how data quality is monitored and maintained.
• Data preparation for AI or analytics initiatives: We clean, structure, and enrich your data to make it AI-ready — increasing reliability and performance of models and dashboards.
• Support for cloud migration and data platform selection: We help assess, plan, and execute your move to cloud platforms like Azure, AWS, or GCP — aligning with your digital goals.

Engagement Example:
R&I — reference architecture & ownership model → Execution — implement pipelines, policies, access controls → Rescue — harden quality, close lineage gaps.

Clear visibility enables confident decisions. We build dashboards that are tailored to users — from operations to C-suite — offering real-time insights, simulations, and executive overviews. Whether using Power BI, Tableau, or custom platforms, we turn your KPIs into actionable intelligence.

• Design of role-based KPIs and executive dashboards: We co-create metrics that matter for each stakeholder — from frontline ops to boardroom — ensuring clarity and alignment.
• Power BI, Tableau, or custom tool deployment: We design and deploy visual analytics solutions using industry-leading tools — or custom-built platforms when needed.
• Business simulation models for planning or finance: We build models that simulate outcomes (e.g., pricing, capacity, investment) to support scenario planning and financial agility.
• Real-time visibility tools for operations or strategy: We enable dashboards with live data feeds to monitor key operations, supply chain events, or strategic KPIs in real time.

Engagement Example:
R&I — KPI tree & wireframes → Execution — build Power BI/Tableau with training → Rescue — performance tuning & UX adoption support.

Accurate forecasting is the cornerstone of smart planning. By combining time-tested statistical models with machine learning, we help businesses move from reactive to proactive. This service is essential for reducing waste, improving service levels, and responding faster to changing market conditions — whether in inventory management, pricing strategies, or financial forecasting.

• Demand forecasting improvement (time series, regression, ML models): We apply time series models, regression analysis, and machine learning techniques to improve forecast accuracy and adaptability across business cycles.
• Inventory, pricing, or financial forecasting: We support data-driven forecasting to optimize stock levels, pricing strategies, or budget scenarios — enabling more agile and profitable decisions.
• Forecast accuracy and bias analysis: We identify systematic forecast errors and bias, improving model calibration and confidence in decision-making across your planning teams.
• Integration with supply chain or ERP systems: Our solutions connect predictive models to real-time systems (like SAP or OMP) to ensure seamless data flow and operational alignment.

Engagement Example:
R&I — baseline MAPE/bias, feature/data study, pilot model → Execution — productionize models + ERP/SCM integration → Rescue — recalibrate models, fix data drift.