AI Development Company for Regulated Enterprises

AIVeda is an AI development company that builds private AI systems for organisations that cannot send their data to a public model. Banks, hospitals, lenders, manufacturers and telecom operators work with us when the constraint is not “can AI do this” but “can AI do this inside our security boundary, under our audit trail, on our infrastructure.” Every engagement below runs on that principle. Nothing leaves your environment unless you decide it should.

Our enterprise AI services span four layers: the models themselves, the retrieval and data infrastructure they depend on, the governance that makes them defensible to a regulator, and the deployment engineering that keeps them running in production. Below is what we build, and where to go for detail.

Private AI and LLM Engineering

This is the core of the practice. We build and deploy language models inside your infrastructure rather than calling someone else’s API. Private AI infrastructure for enterprises covers the reference architecture — network isolation, model serving, GPU planning and the operational surface you inherit. Private LLM development and private LLM engineering cover the build itself: base model selection, fine-tuning, evaluation harnesses and red teaming before anything reaches a user.

Not every problem needs a frontier model. Small language models for enterprises and small model engineering cover the cases where a well-tuned smaller model is faster, cheaper and easier to certify — often the right answer for classification, extraction and routing. SLM deployment services handles putting them into production.

Where models need access to your documents, secure RAG systems covers retrieval architecture with permission inheritance, so a model never surfaces a document the person asking was not entitled to see. On-prem deployment and private LLM deployment cover air-gapped and hybrid topologies. Large language model development services covers custom builds from scratch. For earlier-stage decisions, private AI strategy and advisory is where most engagements begin.

AI Services and Consulting

AI consulting is our assessment and roadmap practice: what to build, what to buy, what to leave alone. AI discovery services runs the structured workshop that precedes it, and AI proof of concept turns the output into something working within weeks rather than quarters. Generative AI POC solutions covers the same path for generative use cases.

On the build side: AI agent development for autonomous workflows, agentic workflow automation for multi-step processes, enterprise AI app development for user-facing systems, and AI integration and automation for connecting models to the systems you already run. Machine learning services, predictive AI solutions and predictive intelligence and forecasting cover the non-language side of the practice.

For vision workloads, see computer vision solutions, vision AI and edge intelligence and multisensory vision and safety systems. For content and knowledge work, see generative AI services, GenAI content generation, AI-based content generation and enterprise knowledge intelligence.

Two capabilities matter disproportionately in regulated environments. AI governance and compliance covers model registries, evaluation evidence and the documentation an auditor will ask for. Secure AI deployment and MLOps covers what happens after go-live — drift, retraining, incident response and rollback. Enterprise AI deployment models compares on-prem, private cloud and hybrid against cost and control. Compliance and document intelligence and executive intelligence dashboards cover the reporting layer.

AI Products

Two products run on the LIRA platform and are deployed inside customer environments rather than sold as shared SaaS.

LIRA Voice is our AI voice calling agent. It runs outbound collections, EMI reminders, KYC verification and customer voice workflows in multiple Indian languages, and is used most heavily by NBFCs, digital lending platforms and insurers. Related: AI calling solutions, conversational agent platform, conversational AI solutions and Salesbot for lead qualification.

Watson Hive is our AI interview platform. It automates resume screening, Round-1 interviews and candidate scoring against a fixed rubric, and integrates with your ATS. It is built for high-volume hiring in BPO and IT staffing environments where the bottleneck is interviewer capacity rather than candidate supply.

Other applied products: Kriti for content creation, AIVeda Wordwise for vernacular learning, One Social for social media management, the AI upskill portal for workforce training, the organisational nervous system for enterprise-wide intelligence, and AI stock predictor for financial forecasting.

Industry Solutions

Regulation shapes architecture more than industry does, but the constraints differ enough to warrant separate treatment. Private AI for healthcare and AI solutions in healthcare cover HIPAA-aligned deployment, clinical documentation and virtual health assistants. Private AI for finance, BFSI AI solutions, fintech AI development and automated claims processing cover lending, insurance and capital markets.

Also: private AI for manufacturing and AI-powered manufacturing solutions, private AI for telecom, AI for eCommerce, AI for education, AI for real estate, agritech AI, AI in mental health monitoring, the mental health support bot and advanced analytics with GNN and KNN.

Data and Cloud Engineering

Most AI programmes stall on data, not models. Enterprise data services is the entry point, covering data modernisation, ETL and ELT, orchestration, real-time streaming, governance, visualisation, end-to-end data solutions and data intelligence. Advanced data security and AWS Glue services cover protection and managed pipelines.

On infrastructure: cloud consulting, cloud advisory, implementation, cloud operations, cost optimisation and cloud security and compliance. Engineering practice is covered by DevSecOps consulting, security in the DevOps pipeline, CI/CD consulting, Python development and analytical engine services.

Specialist Engineering Teams

Where you need capacity rather than a full engagement, we place vetted engineers into your team through our offshore development center. Available specialisms include AI developers, machine learning developers, data engineers, data scientists, Python developers, Databricks developers, Kafka developers, Apache Flink developers, AWS developers, Node.js developers and DevOps engineers.

How Engagements Start

Most begin with a scoped assessment rather than a proposal. We review your data estate, your regulatory constraints and the use case you have in mind, then tell you whether private AI is the right answer — including when it is not. If it is, you get an architecture, a deployment model and a cost envelope before any build commitment.

Proof of what this looks like in practice is in our case studies. Background on the team is on the about page, and common procurement and security questions are answered in the FAQ.

Ready to scope something? Talk to an AI architect or email hello@aiveda.io.