CMARIX provides predictive analytics consulting services to businesses that require predictive forecasting, scoring, and propensity modeling, and not general business intelligence reports. Our consultants build predictive models using your past data, test them against real-world business key performance indicators, and implement them in the systems your business already uses.
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Trusted by 2000+ Happy Clients, Including Fortune 500 Companies
CMARIX delivers predictive data analytics services across the full modeling lifecycle. Every predictive analytics solution is scoped to a business outcome, deployed to production, and maintained for accuracy.
Custom models built on your data, validated against your business benchmarks.
We develop and validate various types of predictive models, including churn modeling, customer lifetime value modeling, propensity modeling, credit risk modeling, fraud risk modeling, and demand forecasting. All of these models are based on your past data and are validated against the pre-agreed accuracy threshold.
Stack: Python | Scikit-Learn | XGBoost | LightGBM | CatBoost | AWS SageMaker | MLflow
Predictions are only as good as the features that drive them.
We review your raw data for data quality issues, coverage gaps, and compliance gaps to engineer the features required by your model. Our data engineering services provide the data infrastructure you need to get clean, labeled data as inputs for predictive analysis.
Stack: dbt | Apache Spark | Airflow | Feast Feature Store | Pandas | Great Expectations | Snowflake
Managed predictive scoring delivered as a turnkey API.
We package your predictive models into a managed scoring service in the form of an API which receives your transactional or event data and outputs a ranked, scored response. The API is called by your CRM, help desk, or marketing tool and provides you with a score indicating propensity, risk, or likelihood of churn. Predictive models need to be refreshed and monitored.
Stack: FastAPI | Kubernetes | Docker | Redis | AWS Lambda | Grafana | Evidently AI
Detects equipment failure before it stops production.
We build sensor data models that predict component failure windows, maintenance priority scores, and remaining useful life estimates, integrated with your SCADA, MES, or CMMS platform. Every model is trained on your machine's historical fault and sensor data and validated on real failure events before deployment.
Stack: Prophet | XGBoost | InfluxDB | Apache Kafka | Grafana | AWS IoT | scikit-learn
Accurate, actionable demand signals at SKU, store, and region level.
We develop demand forecasting models for future sales volume, inventory, and resources across product categories, geographies, and time periods. Each forecast is backed by a confidence interval and directly embedded in your ERP and/or supply chain planning system. Make forecasts productized in your executive dashboard with our data visualization consultancy service.
Stack: Prophet | NeuralProphet | ARIMA | N-BEATS | LightGBM | Databricks | dbt | Power BI API
Embed predictive scores where decisions actually get made.
We connect predictive model outputs, scores, probabilities, and ranked recommendations to the CRM, marketing automation, helpdesk, and BI tools your teams use every day. For predictive analytics packaged as a user-facing application, see our AI application development services for the full product build.
Stack: Salesforce API | HubSpot API | Snowflake | BigQuery | Tableau Embedded | Power BI API | FastAPI
CMARIX builds predictive analytics solutions across model types and industries, each engineered to deliver a specific, measurable business output.
Structured, milestone-driven process that starts with a business problem and ends up with the deployment of a proven predictive model.
The first step is to transform the business problem into a modeling objective and define the KPI that the model will move. No data manipulation begins until the objective is clearly stated.
Timeline: Week 1-2
Deliverables: Objective statement · Target KPI · Baseline metric · Stakeholder sign-off
We assess your data in terms of volume, signal quality, coverage gaps, and compliance posture. We identify feature candidates likely to predict your target outcome.
Timeline: Week 2-3
Deliverables: Data inventory · Quality scorecard · Feature candidates · Gap analysis · Compliance checklist
We build our features, train and tune the competing models, and test them against our agreed accuracy benchmark. No model progresses beyond this step unless it passes the benchmark.
Timeline: Week 3-10
Deliverables: Feature pipeline · Model selection matrix · Training logs · Benchmark results
Validation and business impact analysis using holdout testing and backtesting is carried out to prove the expected ROI to the stakeholders before going into production.
Timeline: Week 8-12
Deliverables: Evaluation report · Business KPI uplift estimate · Backtesting results · Stakeholder sign-off
The model is then deployed as a production API, connected to your target applications (CRM, ERP, BI platform), and tested for performance under load. The monitoring and retraining pipelines are launched on the same day as the model.
Timeline: Week 10-14
Deliverables: Production API · Integration connectors · Load test results · Monitoring setup · Runbook
We monitor for model drift, run scheduled retraining cycles, and report monthly on KPI performance. Predictive models degrade as data distributions shift, and we manage that actively.
Timeline: Ongoing
Deliverables: Drift alerts · Retraining logs · Monthly performance reports · Roadmap reviews
CMARIX builds predictive analytics solutions that enterprise risk, legal, and compliance teams can audit, explain, and defend. Every model ships with documentation, explainability outputs, and governance controls appropriate to its regulatory context.
CMARIX engineers select modeling frameworks, platforms, and tooling based on your data environment, latency requirements, and scale, not default preference.
CMARIX delivers predictive analytics solutions tuned to the data environments, compliance requirements, and decision workflows of each industry.
Healthcare organizations are adopting predictive analytics to make clinical and operational decisions more proactive. CMARIX develops predictive models for patient readmission, disease risk, treatment outcomes, hospital capacity, and claims analysis. Solutions integrate clinical, operational, and patient data to identify patterns that support earlier intervention and better resource planning. With privacy, security, and regulatory requirements considered throughout development, predictive analytics solutions support healthcare providers in improving care delivery while maintaining reliable and responsible data practices.
Dive Into More
CMARIX has a team of dedicated predictive analytics consultants that deliver business KPI led predictive analytics consulting that turns your data into measurable outcomes. Our consultants handle domain specific model development, production deployment and enterprise integration, along with model governance and post deployment MLOps. Every solution is built to improve forecast accuracy, reduce churn, manage risk, optimise inventory, or streamline operations.
Predictive Models Deployed
In-House Data Scientists and Engineers
Client Retention Rate
Years in Product Engineering
CMARIX structures predictive analytics consulting services engagements to match your stage, from validating a single model to deploying an enterprise-wide scoring platform.
Validate one predictive use case against your real data. CMARIX scopes the problem, audits the feature set, trains a baseline model, evaluates it against domain benchmarks, and delivers a clear investment recommendation.
What you get:
Baseline model · Accuracy benchmark · Data readiness report · Feature importance analysis · Investment decision framework
A dedicated and experienced team of developers, predictive analytics consultants, ML engineers, and data engineers builds, validates, and deploys your production scoring pipeline with full system integration and 90-day post-launch support.
What you get:
Production predictive model · Feature pipeline · Integration APIs · Evaluation framework · MLOps setup · 90-day post-launch support
A multi-model scoring platform with shared feature infrastructure, centralized model registry, governance documentation, explainability reporting, and SLA-backed ongoing MLOps for enterprise-scale predictive analytics.
What you get:
Multi-model platform · Feature store · Model registry · Governance documentation · Explainability reports · SLA-backed ongoing support
The cost of running a concentrated AI Proof of Concept Development sprint is between USD 10,000 and USD 20,000 and takes three to five weeks. The cost of a full production pipeline, including system integration, is between USD 30,000 and USD 90,000 and takes two to five months. Multi-model platforms for enterprises start from USD 100,000. All engagements have milestone-based pricing.
A proof of concept typically takes 3 to 5 weeks. Production-ready predictive analytics solutions generally take 2 to 5 months, depending on data quality, integration complexity, and the number of models being deployed.
Most engagements require at least 12 to 24 months of historical transactional, behavioral, or event data at sufficient volume for the target outcome. CMARIX runs a data readiness audit at the start of every engagement to assess what you have and advise on gaps before any modeling begins.
Model accuracy gets affected as data distribution changes in the real world. CMARIX handles this problem with the same diligence it uses to build its models.
Absolutely! Integration is an integral part of every CMARIX project. We develop production APIs to feed our scores and predictions into Salesforce, HubSpot, Snowflake, BigQuery, Tableau, Power BI, and any other proprietary platform you use for decision-making.
We build explainability into every production model using feature importance analysis, confidence scores, and decision explanations. This enables business users to understand why a prediction was made while supporting compliance and audit requirements.
Model accuracy gets affected as data distribution changes in the real world. CMARIX handles this problem with the same diligence it uses to build its models.
You retain full ownership of your data, trained models, source code, and intellectual property. CMARIX delivers complete documentation, deployment assets, and knowledge transfer, ensuring your team has full control after project completion.
Your unique concepts will be crafted into a remarkable end result by our team.
