
Artificial Intelligence & ML Services
Build production AI that delivers
measurable business outcomes

Artificial Intelligence & ML Services
Artificial Intelligence & ML Services
At Sigmacro Technologies we design, build and operate production-grade AI systems that turn data into repeatable business advantage. We combine deep data engineering, modern MLOps, domain expertise and responsible AI practices to deliver predictive, prescriptive and generative solutions—from pilot to enterprise roll-out.
We start by aligning AI initiatives to business KPIs and creating a phased, high-impact roadmap. This includes data maturity assessment, ROI modeling, use-case prioritization and a governance plan that covers lineage, stewardship and privacy. We also design the enterprise data foundation (lakehouse, feature stores, metadata/catalogs) so models train on trusted, auditable data and integrate seamlessly with operational systems.
Our teams develop bespoke ML and DL models supervised, unsupervised, time-series, graph, and generative models—using best-practice pipelines for feature engineering, hyperparameter tuning and bias control. We build models for classical prediction (fraud, demand), computer vision (defect detection, medical imaging), NLP (summarization, intent, retrieval-augmented generation) & recommenders, always optimizing for latency and throughput.
We operationalize models with production-grade MLOps: feature stores for consistency between training and serving, model registries, experiment tracking, CI/CD for models, canary/circuit-breaker deployments, autoscaling inference clusters and GPU/CPU orchestration. Continuous monitoring detects drift, data skew and performance regressions; automated retraining pipelines restore model quality and maintain SLA-backed reliability.
We embed AI into business workflows—real-time scoring in event streams, batch decision services, RAG-enabled knowledge systems, intelligent automation (RPA + AI), and decision engines connecting models to orchestration and human-in-the-loop review. Every AI output includes confidence, rationale & lineage so downstream teams can trust, validate and act on insights. We deliver closed-loop systems where outcomes feed back to improve models & rules.
We work across cloud and open-source ecosystems to choose the right stack for scale and cost-efficiency: model frameworks (TensorFlow, PyTorch, Hugging Face), MLOps (MLflow, Kubeflow, Seldon/Triton), feature stores, data platforms and orchestration (Spark, dbt, Airflow), and cloud providers for managed AI services and elastic inferencing. Our engineers package models into secure APIs, serverless endpoints, or microservices for robust integration with product systems.
Sigmacro embeds governance from day one: policy-as-code, cataloging and lineage, access controls (ABAC/RBAC), encryption, key management and auditable model decision logs. We implement bias detection and mitigation, explainability tools, model risk management, and privacy-first techniques (tokenization, masking, synthetic datasets, differential privacy) to satisfy legal, regulatory and ethical standards for healthcare, finance and public sector deployments.
We adopt security-by-design: encrypted data pipelines, role-based access, secure model serving, and secrets management. Privacy controls (tokenization, anonymization, differential privacy) and bias-checking are part of model lifecycles; for regulated industries we provide documentation and explainability outputs for auditors and regulators.
Projects designed to improve KPIs (revenue, cost, NPS) not just technical proofs.
Production SLAs, rollback plans, monitoring and incident automation.
Audit trails, explainability, and compliance alignment for sensitive sectors.
PoC → pilot → scale within months using accelerators and templates.
Continuous retraining and value measurement to protect long-term ROI.
playbooks, training, and knowledge transfer so your team owns the solution.
We deployed enterprise-grade virtual assistants with retrieval-augmented generation (RAG) connected to internal knowledge bases and policies. The assistant handled routine HR, IT and customer service queries with escalation workflows and human-in-loop validation for compliance-sensitive responses. The result: 70%+ automation of tier-0 queries, faster employee onboarding, and consistent policy-compliant answers.
A national D2C brand engaged us to maximize revenue during peak seasons. We unified web, app and offline signals into a CDP, built product-level propensity models, and used dynamic creative optimization to personalize hero banners and ad creatives in real time. Programmatic retargeting and email flows were orchestrated to capture cart abandoners with AI-optimized discounts. Simultaneously, CRO work on PDPs and checkout flows removed friction. The campaign produced a 5x uplift in holiday sales velocity.
We implemented a unified customer 360 that fed a feature store for real-time recommendation, propensity scoring and campaign orchestration. Dynamic creative optimization and A/B testing integrated with programmatic buys and on-site personalization, increasing average order value by 20–30% and lift in repeat purchase by 25% within months. The platform’s cold-start problem was mitigated via hybrid collaborative/content models and contextual signals.
Whether you have questions, need support, or want to explore business opportunities, our team is here to assist you.
+91-90682135009
business@sigmacro.com
India | London UK | Delaware USA
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