Generative AI integration & Intelligent Agent Engineering for companies that move fast

Azranta helps data-driven insurers, banks, and life-science teams ship custom LLM agents that cut 30-50 % of busywork, unlock new revenue streams, and keep sensitive data inside your walls


What We Deliver

Generative AI That Ships Real Business Value

From custom LLMs to agent-driven workflows, Azranta blends deep ML craft with bullet-proof delivery to turn Gen AI hype into hard savings and new revenue.

Prototype in Days

Spike out a low-risk sandbox to prove ROI fast—no enterprise-grade red tape


Conversational Agents

Bank-grade chat/voice bots with guardrails, audit trails, and zero-leak knowledge bases

Predictive & Prescriptive Analytics

Replace rear-view reports with forward-looking demand, risk, and cash-flow forecasts powered by your data lake

Product Boosters

Inject code-generation, defect triage, or content co-pilots straight into existing apps to 10× feature velocity


Ops on Autopilot

Draft, summarize, and route docs end-to-end—freeing teams from low-value clicks and cutting cycle times in half


Task-Crushing AI Agents

Plug them into your stack, slash cycle times, and watch new capacity appear. Modular, secure, and fully observable, so one agent today scales to a fleet tomorrow

Smart Factory Vision AI

20 % Fewer Surveillance Hours, Zero Blind-Spots

We deployed an on-prem “Vision Hub” that identifies every visitor, vehicle-plate, and PPE violation in real time— slashing manual clip-review and tightening audit trails.

20 % guard time – AI flags only true exceptions
95 % plate-read accuracy across 6 gates
80 %+ face-match for visitor authentication
58 % faster QA reporting with auto-generated incident logs

AI Computer Vision

Reduced Inspection Costs and Time by over 28% for Property Inspectors

We utilized Generative AI to analyze a large dataset of NVMS property photos to detect anomalies and built a conversational AI chatbot for efficient customer service.

Deep learning and computer vision driven image data extraction
GPT-based NLP chatbot for enhanced customer experience
Improved work efficiency by 80%
Image classification for detecting anomalies

Why Us

How Azranta Builds a Generative-AI Solution That Actually Ships

At Azranta, “cool demo” isn’t the finish line. We follow a five-step playbook that turns Gen-AI proofs of concept into revenue-grade products—fast, secure, and built to scale.

Tune the Data, Turbo the Results

We roll up our sleeves on raw data—deduping, labeling, and enriching until every record is model-ready. Noise out, signal in.

Lock-Tight Security from Day One

Zero-trust access, field-level encryption, and on-prem/sovereign-cloud options. Your IP stays yours—full stop.

Test, Tune, Outperform

We torture-test models across edge-case datasets, bias probes, and red-team prompts, then fine-tune for precision and recall.

MLOps That Runs 24/7—So You Don’t Have To

Automated pipelines handle retraining, versioning, and rollback. Real-time dashboards flag drift before it bites.

Scale Without Sticker Shock

Quantization, pruning, and smart caching cut GPU burn by up to 40 %. Horizontal autoscaling keeps latency low during demand spikes.

Tools and Technologies

Generative AI development Tech stack we use

Before we begin the Generative AI model development process, we help organizations with data analysis, cleaning, organizing, preparation and turn it into a format that is suitable for custom Generative AI solutions. This may include normalizing or standardizing numerical data, encoding categorical data, and possibly generating new features through various transformations to enhance model performance.

DL Frameworks

Cloud Platforms

Generative AI Models

Libraries

Neural Networks
CNN & RNN

Metric Learning algo

Our Partners

Partnering with the Ecosystem to Make
Development Easier

Before we begin the Generative AI model development process, we help organizations with data analysis, cleaning, organizing, preparation and turn it into a format that is suitable for custom Generative AI solutions. This may include normalizing or standardizing numerical data, encoding categorical data, and possibly generating new features through various transformations to enhance model performance.

Microsoft

Google

Amazon

Contact us today to explore limitless possibilities with our Generative AI development services.

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