Services
Production-grade AI — copilots, automation and intelligent workflows scoped to measurable outcomes.
01 · Core
GPT copilots, content and code assistants grounded in your private data.
02
AI Chatbots
Support and internal assistants with RAG, human handoff and analytics.
03
Machine Learning
Forecasting, classification and custom models trained on your datasets.
04
NLP
Search, summarisation, sentiment and document understanding at scale.
05
AI Automation
Workflow agents that complete tasks across CRM, ERP and internal tools.
06
AI Integration
Embed models into existing software, APIs and customer portals.
Overview
Pventra Technologies Pvt. Ltd. designs and deploys production-grade AI systems — from GPT-powered copilots and NLP pipelines to computer vision and workflow automation. We help startups and enterprises turn data into measurable outcomes with secure, scalable AI architecture.
Audience
SaaS products adding copilots
Enterprises with private knowledge bases
Ops teams automating support and back-office work
Use cases
01
Ask-your-docs assistants for sales, legal, HR and engineering — grounded in your files, not the public web.
02
Ticket deflection, suggested replies and human handoff with transcripts and quality scoring.
03
Extract, classify and summarise contracts, invoices and claims at volume.
04
Forecasting, scoring and anomaly detection trained on your operational data.
Deliverables
01
Scoped use-case document and data-readiness notes
02
RAG / model architecture and prompt library
03
Production service with auth, logging and cost controls
04
Eval set, monitoring dashboard and runbook
05
Handover and optional managed improvement sprints
Stack
AI delivery
Data, evals and guardrails first — then a pilot that can actually ship.
Use cases, data readiness, compliance and ROI targets.
Model choice, RAG architecture, prompts and integration map.
POC to production with evals, guardrails and human-in-the-loop.
Deployment, observability, cost controls and handover.
Fine-tuning, new workflows, analytics and scale.
Engagement
Pick one workflow with a measurable KPI — deflection, hours saved or conversion.
Sources, PII rules, retrieval design and what the model is not allowed to do.
Working copilot or pipeline with evals and a named owner on your side.
Latency, cost caps, audit logs and integration into CRM or your product.
Weekly quality review, prompt/model updates and new workflows.
FAQ
Yes. We design RAG systems, fine-tuned models, copilots and internal knowledge assistants using OpenAI, Azure OpenAI and open-source LLMs.
Absolutely. We add AI features to CRMs, ERPs, support desks and custom platforms without a full rewrite.
Not always. Many copilots start with RAG over existing documents. Custom ML is used when you have enough historical outcomes to train on.
Grounding, citations, refusal rules, human-in-the-loop for high-risk actions, and evals against a golden set.
Yes. We deploy on Azure OpenAI, AWS Bedrock or self-hosted models depending on data residency.
