Matrida builds AI agents, knowledge assistants and automation that do real work inside your business, with the quality, security and cost controls that demos skip.
Illustrative interface with sample data.
At a glance. Matrida Infotech is an AI-first IT services company. Its services: AI Agents, RAG Assistants, GenAI Apps, AI Automation, LLMOps, AI Strategy Sprint, Creative AI, Recommendation Engines, Conversational AI, Predictive AI, Computer Vision, Voice AI, Custom LLMs, AI Evals and Guardrails, Inference Engineering, On-Device AI, Private AI Deployment, Document AI, Data and Labelling, AI Products, for growing businesses. It works with clients remotely.
We build AI agents that complete multi-step work inside your systems, with guardrails, human approval and full audit logs.
Learn more →02Private assistants that answer from your documents with citations, permission-aware retrieval and measured accuracy.
Learn more →03Customer-facing and internal LLM products, from document drafting to AI copilots inside your SaaS.
Learn more →04Automate document-heavy, judgement-light work across finance, HR, support and operations.
Learn more →05Evaluation, monitoring, cost tracking and release processes that keep AI systems reliable after launch.
Learn more →06A fixed two-week sprint that gives you a ranked use-case list, a working proof of the top idea and a costed plan.
Learn more →07We build generative systems that produce on-brand text, images, video and audio, with review steps and safety checks built in.
Learn more →08We build recommendation systems that learn from behaviour and preference, and prove their lift with controlled tests.
Learn more →09Assistants that understand context, answer from your knowledge and know when to hand over to a person.
Learn more →10We turn your historical and live data into forecasts, risk scores and early warnings, with honest measures of how often they are right.
Learn more →11Systems that read images and video: detect objects, check quality, track movement and run on cameras or at the edge.
Learn more →12Real-time voice interfaces with accurate recognition, natural speech and conversation that does not feel like a phone tree.
Learn more →13Domain-specific language models fine-tuned or distilled on your data, measured against your tasks, and delivered on weights you own.
Learn more →14Know whether your AI works before you ship it, and keep knowing after: evaluation suites, red-teaming, guardrails and live monitoring.
Learn more →15Serving stacks tuned for speed and cost: quantisation, batching, caching, speculative decoding and GPU planning, measured on your own traffic.
Learn more →16Small language, speech and vision models running on phones, laptops and edge hardware, with no cloud round trip and no data leaving the device.
Learn more →17AI that runs where your data must stay: on your servers, in your private cloud or inside your country, with access control, audit logs and monitoring.
Learn more →18Invoices, claims, contracts and forms read, checked against your rules and filed into your systems, with uncertain fields sent to a person.
Learn more →19The datasets AI learns from and is tested on: annotation with quality control, synthetic data for rare cases, and evaluation sets that mirror production.
Learn more →20AI-native web, mobile and API products designed around what the model can and cannot do, shipped and maintained by one team.
Learn more →Getting a model to answer is the easy part. Everything around it is the work, and that is what we do.
Evaluation, security and cost are planned on day one, because that is where AI pilots die.
Every project starts with a baseline and a target you agree to, so the result is a number.
We pick models on evaluation results and keep you free to switch providers.
Code, prompts, evaluation data and documentation are yours, with a real handover.
30 minutes, free. We tell you honestly if AI is the right tool.
Two weeks: ranked use cases, a prototype on your data, a costed plan.
6 to 12 weeks with real users, measured against your baseline.
Roll out, monitor and improve, or take it in-house with a full handover.
We do not hand you a deck and disappear. We build, test, launch and, if you want, run the system. Every engagement ends in something working and a handover, not a slide set.
We do not spend weeks learning your space. We rank your ideas by value, risk and data readiness, test the best one on your own data, and write down what "working" means before anything is built.
Outcome One use case worth building, with a number to beat and an honest no for the rest.
Models are only as good as what they are given. We connect your documents and systems, set access rules, clean what matters and design the context each task needs, so answers come from your facts.
Outcome A knowledge and data layer the AI can rely on, with permissions that hold.
We build the smallest system that can win, with an evaluation set from your real cases running on every change. Prompts, models and tools are chosen by the scores, not by taste.
Outcome A pilot in front of real users, scored against the baseline you agreed.
Shipping is the start. We add monitoring, cost budgets and fallbacks, watch real usage, and fix what the numbers show, or hand the whole thing to your team with documentation and training.
Outcome A system that keeps getting better after launch, at a cost you can see.
| Service | Industries | Core stack |
|---|---|---|
| AI Agent Development | Financial Services, Retail & E-commerce, Manufacturing, Logistics & Supply Chain | Claude, GPT, Gemini and open-weight models · Python · Temporal · tool-calling APIs · Langfuse |
| RAG & Enterprise Knowledge Assistants | Financial Services, Healthcare, Manufacturing | PostgreSQL + pgvector · hybrid search and reranking · LlamaIndex or LangChain · Claude or GPT |
| Generative AI Application Development | Healthcare, Retail & E-commerce, Logistics & Supply Chain | Next.js · Python (FastAPI) · streaming LLM APIs · model routing · prompt and eval tooling |
| AI Workflow Automation | Financial Services, Healthcare, Retail & E-commerce, Manufacturing, Logistics & Supply Chain | n8n · Python · LLM extraction · ERP, CRM and email APIs · exception dashboards |
| MLOps & LLMOps | All industries | Langfuse or OpenTelemetry tracing · evaluation harnesses · CI/CD · cost and latency dashboards |
| AI Strategy Sprint | All industries | Use-case scoring · data and security review · build-vs-buy analysis · pilot plan |
| Generative and Creative AI Development | Retail & E-commerce | Stable Diffusion · Google Veo · Gemini · Stability AI · ElevenLabs · human review workflow |
| Recommendation Engine Development | Retail & E-commerce | Scikit-learn · TensorFlow Recommenders · Amazon Personalize · feature store · A/B testing |
| Conversational AI and Chatbot Development | Financial Services, Healthcare, Retail & E-commerce | OpenAI · Gemini · LangGraph · Qdrant · n8n · channel connectors |
| Predictive AI and Forecasting | Financial Services, Retail & E-commerce, Manufacturing, Logistics & Supply Chain | Scikit-learn · PyTorch · Prophet · Darts · SciPy · Tableau |
| Computer Vision Development | Healthcare, Retail & E-commerce, Manufacturing, Logistics & Supply Chain | OpenCV · PyTorch · Ultralytics YOLO · TensorRT · Google Cloud Vision · Amazon Rekognition |
| Voice AI Development | Financial Services, Healthcare, Logistics & Supply Chain | LiveKit · Vapi · ElevenLabs · OpenAI Realtime API · Deepgram · telephony connectors |
| Custom LLM Training and Fine-Tuning | All industries | PyTorch · Hugging Face · LoRA and QLoRA · vLLM · open-weight models · Weights & Biases |
| AI Evals, Red-Teaming and Guardrails | Financial Services, Healthcare | Langfuse · Promptfoo · Ragas · LangSmith · policy and PII filters · OpenTelemetry |
| Inference Engineering and Optimisation | Retail & E-commerce, Logistics & Supply Chain | vLLM · TensorRT-LLM · llama.cpp · Triton · Kubernetes · load-testing harnesses |
| On-Device and Edge AI | Manufacturing, Logistics & Supply Chain | llama.cpp · ONNX Runtime · TensorFlow Lite · Core ML · ExecuTorch · edge GPUs and NPUs |
| Private and Sovereign AI Deployment | Financial Services, Healthcare | Kubernetes · Terraform · vLLM · Vault · Prometheus · Grafana · open-weight models |
| Document AI and Intelligent Processing | Financial Services, Healthcare, Manufacturing, Logistics & Supply Chain | Vision-language models · OCR engines · Azure Document Intelligence · AWS Textract · schema validation |
| Data, Labelling and Synthetic Data | Manufacturing | Label Studio · CVAT · Argilla · Great Expectations · dbt · PII redaction tools |
| AI Product and Platform Development | Retail & E-commerce | Next.js · React Native · FastAPI · PostgreSQL · vector databases · Stripe · cloud hosting |
Instant results in your browser. No sign-up needed to see your number.
Ten questions across strategy, data, tech, people and governance.
Open the tool →Savings, payback and first-year return for any automation idea.
Open the tool →An indicative budget and timeline from five project drivers.
Open the tool →Eight questions that point to build, buy or hybrid.
Open the tool →Monthly API spend by volume, tokens, model tier and caching.
Open the tool →Score up to five AI ideas and see which one to build first.
Open the tool →A practical PDF for CTOs, founders and product leaders.
AI for banks, NBFCs, insurers and fintechs, with the audit trails and data controls regulated teams need.
See use cases →Healthcare AI that reduces administrative load for hospitals, clinics and health-tech products.
See use cases →AI for online and omnichannel retail: conversational commerce, catalogue enrichment and support automation.
See use cases →AI for manufacturers: maintenance knowledge, quality inspection, supplier documents and procurement.
See use cases →AI for freight, 3PL and supply chain teams: document automation, exception handling and shipment communication.
See use cases →Why AI pilots stall and the seven-stage method that gets them into production. For CTOs, founders and product leaders.
Get the PDF →Technical whitepaperA reference design for enterprise knowledge assistants, covering ingestion, retrieval, permissions and evaluation.
Get the PDF →ChecklistForty yes-or-no checks across strategy, data, technology, people and governance. Finish it in 20 minutes.
Get the PDF →We design, build and run production AI systems: AI agents, RAG knowledge assistants, generative AI applications and workflow automation, plus the operations layer that keeps them reliable.
It depends on scope, integrations and risk. Our free AI project cost estimator gives an indicative range in two minutes, and a strategy call will narrow it down.
Our Strategy Sprint gives you a working prototype on your data in two weeks. A focused production pilot usually takes 6 to 12 weeks.
Yes. You own the code, prompts and evaluation sets we write for you. Your data stays yours and is never used to train models.
We are vendor-neutral and choose on evaluation results, using hosted models from major providers or self-hosted open-weight models when your data rules require it. Our designs keep you free to switch.
We draw the data flow on one page, apply least-privilege access, redact personal data where needed and use terms that exclude training on your data. We involve your security team in the first week.
Tell us what you want AI to do. An engineer replies within one business day with a clear verdict: go, not yet, or not with AI.
You also get the AI Project Playbook (PDF) straight away.
