Most AI projects fail not because of the model — they fail because they sit on the side of the business, disconnected from the policy admin, the loan origination or the CRM where the real decisions happen. Redian Software builds AI/ML that lives inside the workflow. We are CMMI Level 3 Appraised, ISO 27001 and 9001 certified, and have shipped for 200+ enterprises over nine years across Noida, Nairobi, Dubai, London and New York — with data scientists who sit inside BFSI and insurance domain teams rather than a generic AI lab.
What we build
Production AI grounded in your data and embedded in the systems running your business:
- Generative AI agents — customer-service copilots, underwriter and adjuster assistants, RFP responders, contract analysers. Retrieval-augmented generation built on your documents, with citation-first UX and human-in-the-loop review where the risk demands it.
- ML pricing and rating engines — insurance motor, health and property pricing, credit scoring, dynamic loan pricing, propensity-to-buy models embedded in the quote flow.
- Intelligent document processing — KYC, claims, policy documents, contracts, bank statements. OCR plus LLM extraction with confidence scoring and structured hand-off to case management.
- Fraud, anomaly and monitoring models — payment fraud, claims fraud, transaction monitoring, identity anomaly, adverse-event detection.
- Predictive analytics — churn, default, arrears, NPS, capacity planning, portfolio stress models.
- Computer vision — asset inspection (solar, transmission, distribution), document capture, damage assessment.
Who we build this for
- Banks, NBFCs and lenders embedding scoring, fraud and collections models
- Insurers, MGAs and brokers deploying pricing, claims triage and document extraction
- Enterprise operations groups adding predictive maintenance and CV-assisted inspection
- Product companies bolting AI features onto their SaaS without hiring a full research team
- Regulated firms that need explainability, bias testing and reproducible training pipelines
Our approach
Discovery — problem framing, data audit, feasibility spike and success metrics tied to a business KPI, not model accuracy in isolation. Prototype — a working evaluation notebook against real data (in a secure enclave), baseline model, and a defensible decision on build vs API vs hybrid. Engineering — production data pipelines, model training and evaluation harness, deployment inside your VPC (or ours), and MLOps from day one — versioned datasets, evaluation gates, drift monitoring, rollback. Integration and UAT — model surfaced in the actual workflow (CRM, PAS, LOS, contact centre), with human-in-the-loop where policy requires. Go-live and monitoring — evaluation dashboards, drift alerts, quarterly re-training cadence. Timelines committed at the end of Discovery, in writing.
Why Redian for AI/ML
- CMMI Level 3 Appraised, ISO 27001 and 9001 — controls the model risk team asks about.
- Domain-embedded data scientists — BFSI, insurance, energy and retail engineers, not lab hires learning your business on your dime.
- 9+ years and 200+ enterprises — production ML in supervised environments, not just POCs.
- MLOps and explainability by default — SHAP, LIME, dataset provenance and model cards for regulator conversations.
- Model-neutral — OpenAI, Anthropic Claude, Bedrock, Vertex AI, self-hosted LLaMA, Mistral and fine-tuned open models. We choose per use case, not per vendor discount.
- Multi-region delivery — Noida, Nairobi, Dubai, London and New York.
Where we have delivered
AI and ML programmes across India, Kenya, UAE, UK, USA, Canada and Australia, with focused work in Nigeria, Tanzania, Uganda, Ghana, Rwanda, Ethiopia, South Africa and Saudi Arabia. Reference deliveries include ML pricing for an African motor insurance aggregator and document-AI for a SuiteCRM KYC programme at an investment bank.
Working with Redian
Tell us the use case, the data you have, and the KPI you need to move. We come back inside one business day with a written first read from a senior data scientist and a feasibility position — build, buy or hybrid — that respects your regulator. NDAs signed on request. Start at /contact or read our AI/ML expertise and case studies.
