AI Services
The AI Practice Built on Engineering Discipline.
From LLM integrations to Agents, SwaaS engineers AI that is accurate, governed, and built to perform in production environments.
AI Capabilities
The Core AI Capabilities Behind Every SwaaS Build
Every AI system SwaaS builds draws from eight core capabilities, each production-tested, each built to work as one connected system.
Why SwaaS
AI Services That Go From
Concept to Production
Four practice areas. Each one covering a distinct AI capability. All of them delivered with the same FTR discipline and governance SwaaS applies to every build.
- RAG
- Conversational AI
- AI Applications
- Legacy Modernization
RAG
SwaaS builds RAG systems that index your enterprise data and make it queryable in plain language. Just accurate answers pulled from your own sources, in real time.
Sub-services:
- Enterprise Data Indexing - Your data, structured, indexed, and ready for AI to retrieve accurately.
- Natural Language Querying - Users query complex data in plain language and get precise, sourced answers instantly.
Conversational AI
SwaaS builds AI systems that hold real conversations and take real actions. From intelligent chatbots to agents that handle multi-step workflows end-to-end.
Sub-services:
- Chatbots - Omnichannel AI assistants built on enterprise LLMs.
- Agentic AI - Autonomous agents that reason, retrieve, and act across complex workflows with human oversight at critical decision points.
AI Applications
SwaaS has built AI applications across four use cases. Each one available as a reference build or customized for your specific environment.
Applications:
- Sales Coach - An AI system that analyzes sales conversations, surfaces coaching insights, and helps reps close faster.
- IDP (Intelligent Document Processing) - Extracts, classifies, and processes unstructured documents with AI accuracy and human-in-the-loop validation.
- Ask-Your-Data - A natural language interface that lets anyone in your organization query internal data without writing code.
- Service Assistant - An AI-powered support agent that resolves queries, escalates intelligently, and learns from every interaction.
Legacy Modernization Powered by Arjun
SwaaS modernizes legacy codebases using Arjun, a six-agent AI pipeline that replaces chaotic, handoff-driven refactoring with a spec-driven, governed system.
What Agent Arjun covers:
- Story + Spec - Business requirements converted into validated, testable specs before a line of code is written.
- Code Analysis - Dependencies mapped, reusable code identified, migration blueprint produced.
- Code Generation - Backend and frontend code generated from the spec,tailored to your existing stack.
- Code Review - Every line of generated code reviewed for correctness, security, and performance. Up to three review cycles run before anything moves to the next stage.
- Integration & Testing - Automated tests run, API contracts validated, data flow integrity confirmed.
- Release Readiness - Deployment packages, migration scripts, rollback plans, and runbooks prepared for go-live.
Data to AI Practice
From
Broken Data to Business That Runs on
Intelligence
Most enterprises sit on data that lives in disconnected systems, structured in different ways, accessible only to specialists. SwaaS connects it, structures it, and builds AI on top of it so your business stops reacting and starts deciding.
Enterprise Data
Raw data from disconnected systems is not AI-ready. SwaaS maps your data landscape, connects the sources, and structures it into a foundation that AI can actually work with.
Foundation Models
Once the data is structured and integrated, SwaaS builds RAG systems and foundation models that extract meaning from the data and surface decisions, not just reports.
Autonomous Agents
With intelligence in place, SwaaS deploys agents that act on it. They handle complex decisions, trigger workflows, and improve with every cycle.
Business Outcomes
The result: faster operations, reduced costs, and teams no longer buried in manual work. Your people focus on strategy. The system handles the rest.
AI Tech Stack
AI Stack Architecture
A layered AI stack architecture built for accuracy, governance, and deployment at scale. Every component is connected, from foundation models to the interfaces your users interact with.
Search and Retrieval
- LangChain
- LlamaIndex
Intent Classifier
- RASA
- Google Dialogflow CX
LLM Providers
- OpenAI
- Perplexity
- Anthropic
- Hugging-Face LLM
Infrastructure
- Docker
- Azure
- AWS Cloud
- Google Cloud
Data Storage
- Pinecone
- SQL Server
- MySQL
- PostgreSQL
- PGvector
- FAISS
Multi- Modal
- Voice
- Text
- Video
- Image
Tech Stack
- React
- Flutter
- GraphQL
- Python
- Node.js
- Fast API
- Langchain
Agent Pipeline
AI-Native Dev
Pipeline, Built by SwaaS.
AI Native Pipeline based on years of delivery experience. Agent Arjun is a development pipeline, a set of agents that turn your development process into a governed pipeline.
Arjun
Our AI-Native
Development Engine
How it Works
What Happens Inside
an AI Agent
Every AI agent SwaaS builds follows the same six-step reasoning loop, from the moment a query arrives to the moment it is resolved, with human oversight.
SwaaS Agents AI combines continuous reasoning, multi-step tool orchestration, and human-in-the-loop governance. The result: self-improving systems that operate within defined guardrails and get more accurate with every cycle.
SwaaS AI Governance
AI That Earns
Trust at Every Layer
SwaaS governs every AI system it builds, from the first commit to the final deployment. Five layers. No exceptions.
Built Bias-Free from the Start
Compliance Before the First Commit
Human Validation at Every Decision Point
Full Visibility into Every AI Action
Governance Baked In
Results That Speak
AI That Moves
the Needle.
Every metric here came from a live engagement, a real client, and a system that went to production.
97%
On-Time Delivery
Every sprint. Every engagement. No exceptions.
20+ Agents Built
Purpose-built, tested, and deployed in live production environments.