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Case Studies

Built and shipped. The full story behind every product.

These are our own products. Each case study shows the real problem we faced, the system we built, and what it delivers today for real users.

Our Products, Proven in Production

The problem, the solution, the impact - for every product we've built.

Each study walks through what we built for our own platform, why, and what it's delivering right now.

6 case studies shown

SaaS PlatformEducationLive

Apar AI LMS

100+

AI workflows

300K+

Learning assets

2 Days

Institution rollout

AI-Native Educational Operating System

Apar AI LMS is the only school LMS built to solve what actually consumes teacher time: creating content, building assessments, checking answers, and delivering learning in students' own languages. The platform takes the educational curriculum and runs it through over 100 AI-powered steps to produce validated lesson plans, question banks, summaries, concept maps, viva sessions, and multilingual study material — all ready before a single teacher logs in.

Core angle

Technology in education, not education on technology

Most EdTech platforms are delivery tools at heart. They move lectures to video, textbooks to PDFs, and tests to dashboards. But the actual teaching work — preparing content, creating assessments, checking student answers, conducting oral exams — still happens manually, outside the platform. Apar AI LMS is built differently. It is not a tool that sits around the edges of teaching; it is embedded inside the process itself. Content generation, lesson planning, assessment, multilingual access, and quality checks all happen within the system. A school that relies on Apar AI LMS cannot simply replace it with a different platform, because the platform is carrying a significant share of the educational workload. That is the real claim: this is not an LMS with an AI chat feature added on. It is a system that takes chapters as input and produces ready-to-use teaching resources, student learning experiences, and scalable assessments as output.

Read Full Case Study Visit aparailms.com

SaaS PlatformEducationLive

Apar Academy

Free chapters per subject

₹99/yr

Launch pricing

Live AI features

B2C AI Study System

AparAcademy gives every student a complete study system for their NCERT curriculum — free chapter access to start, seven AI study features built into the course, oral viva practice, learning in their own language, and gamified progress tracking to keep them coming back. All of it for ₹99 a year.

Core angle

A study system, not another lecture app

The strongest B2C education products do more than host content. AparAcademy connects six layers into one coherent student flow: public discovery, freemium chapter access, AI-guided study, oral viva practice, progress tracking, and gamified retention. Remove AI and the learning behavior changes. Remove freemium logic and conversion breaks. Remove progress memory and retention weakens. The product only works because all six layers reinforce each other — and that coherence is the actual differentiator.

Read Full Case Study Visit aparacademy.com

SaaS PlatformCross-IndustryLive

Apar Chatbot

5 Min

To a live chatbot

Chatbot engines

9-section

Visitor intelligence

AI Chatbot-as-a-Service Platform

Apar Chatbot solves the setup problem that stops most businesses from deploying a useful AI chatbot: there is nothing to train. Register a website URL, and the platform reads every page automatically — learning your product catalog, pricing, support FAQs, and contact details. The chatbot that appears on your site already knows your business. It started reading your website before you finished your coffee.

Core angle

A chatbot you don't train — a platform that reads your website and deploys itself

Most chatbot platforms hand businesses an empty bot and a knowledge-base editor. The assumption is that the business will populate it. In practice, that assumption defeats adoption: if setup requires significant manual work, teams delay, skip corners, and eventually abandon the tool before it helps a single visitor. Apar Chatbot starts from a different premise. A business's website already contains the answers its visitors need — product descriptions, pricing, support information, team bios, policies, FAQs. The job of a chatbot platform is to read that content, turn it into retrievable knowledge, and answer questions from it. Not to present an empty interface and wait. That shift — from 'bring your own training data' to 'we read your site and deploy' — is what makes the platform commercially viable for small and mid-size businesses. The engineering underneath that shift is not simple — automated website reading, strict data separation between customers, usage-based billing, conversation intelligence, WhatsApp integration, and three different chatbot engines for three different situations. But from the customer's side, the experience is: register a URL, wait a few minutes, paste an embed code, done.

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SaaS PlatformEducationBeta

Apar Exam

<2s

Paper assembly

5-node

AI grading pipeline

5 credits

Free monthly tier

B2C Exam Paper Generation & AI Grading Platform

AparExam is a self-serve exam portal for independent educators. Pick a board, grade, subject, and chapters — the platform assembles a curriculum-aligned paper from a 300K+ question bank in under 2 seconds, exports a copy-protected branded PDF, and processes uploaded answer sheets through a five-step AI grading pipeline with OCR, per-question evaluation, and educator override. Generate and grade on credits: 5 free every month to try the full workflow before paying anything.

Core angle

Select your syllabus. Generate the paper. Grade the answers. Done.

Most exam tools solve exactly one problem and stop there. A template editor gives you a blank page. A question-bank browser lets you browse but not assemble. A generic AI prompt box produces exam-looking text once and forgets the context the moment the session ends. An institution-first ERP handles the paper logistics but requires an admin, a contract, and a training cycle before a single educator can use it. None of them connect the full workflow from syllabus selection to completed graded submission. AparExam takes a different position. It is a self-serve educator product that compresses six connected steps — register, select curriculum, generate paper, export protected PDF, upload answer sheets, and review AI grades — into one credit-metered portal. The intelligence underneath is not rebuilt from scratch inside a consumer product. AparExam runs on top of the same paper assembly engine, question bank, and grading tools that power institution-facing products. That architectural choice is commercially meaningful. The portal gets real depth without rebuilding anything from scratch, and individual educators get a tool that behaves like serious exam infrastructure instead of a novelty generator. The commercial model matches educator behavior. Teachers work in bursts around exams, coaching schedules, and academic cycles — not on steady enterprise SaaS timelines. Paying per generation and per grading submission, with a persistent credit balance that does not expire, fits how individual educators actually consume a tool like this.

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SaaS PlatformLegalIn Delivery

Aparsoft LegalOS

Separate

Database Per Firm

10+

Roles & Interfaces

Unlimited

Clients

SaaS Platform

How Aparsoft built a law firm's entire digital practice — public presence, intake, scheduling, engagement letters, matter tracking, a privilege-aware document vault, a client portal and a citation-only AI assistant — as one product where compliance is enforced by the data model rather than by disclaimer copy.

Core angle

The Challenge

Ask a partner where the practice hurts and you will not hear “we need a website.” Indian law firms run on WhatsApp, email attachments and a site nobody has updated since it was built — and the two software categories that could help both fail them. Generic practice-management tools cannot answer the Bar Council of India's advertising rules or the DPDP Act. Agencies build a brochure and hard-code the firm's identity into it, so the second firm costs as much as the first.

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AI PlatformCross-IndustryReady for Demo

FireIQ

2-stage

Detection pipeline

Alert output channels

5-field

VLM scene analysis

AI Fire & Smoke Detection Prototype

FireIQ is a prototype built on Aparsoft's existing video AI infrastructure. It goes past raw detection — combining computer vision object detection inference, optional false-positive suppression, VLM-based scene reasoning, multi-channel alert fan-out, and a full evidence trail — into one demo-ready operator flow. The honest claim: detection alone was never the hard part. Building a coherent incident workflow around it is.

Core angle

Detection is the beginning, not the product

Most fire monitoring demos stop at a bounding box on a frame. That is not a workflow. A facility team seeing a box on a screen still has to decide: is this real? How serious? Who do we call? What do we tell them? FireIQ was built to answer those questions inside the same system — not across five separate tools or a human chain. It runs a real event loop: ingest, detect, smooth, reason with a VLM, fan out the alert, and log the evidence. The prototype is honest about what it is — not a hardened production platform — but it proves the pipeline is sound and the next phase of engineering now has a concrete foundation to build from.

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Technology Stack

Built on Enterprise-Grade AI Infrastructure

Our platform combines cutting-edge AI technologies with battle-tested infrastructure to deliver reliable, scalable solutions.

LLM Integration

OpenAI, Anthropic-Claude, Open-Source LLMs with LangGraph agentic workflows and validator agents

Vector Databases

PostgreSQL + pgvector with multi-tenant collection isolation for semantic retrieval

Scalable Backend

Django REST + FastAPI microservices with Celery task queues and Docker deployment

Enterprise Security

HMAC-SHA256 webhooks, JWT auth, RBAC, and compliance-ready infrastructure

aparsoft_stack_architecture

AI / LLM Layer

OpenAI

Anthropic-Claude

Open-Source LLMs

LangGraphLangChainValidator Agents

Application Layer

Django REST

Next.js 16+

Celery Workers

WebSocket

Data & Infrastructure

Databases

VectorDB

Redis

Cloudflare R2Bunny CDNRazorpayBhashini

Production Infrastructure

5 products deployed on this stack