Workflows Use Cases Industries Product
Chittaa Labs Private Limited

We design & engineer
AI Agent Workflows
that actually work.

"A true AI Agent Workflow cannot be built with AI"

— Not written by AI
10 Workflow Patterns
30+ Real-world Scenarios
6 Industries Served
∞ Possibilities
What We Build

AI Agent Workflow
Architectures

From simple sequential chains to multi-agent debate systems — we engineer the exact architecture your problem demands.

01 Sequential
Prompt Chaining
Break complex tasks into sequential steps where each LLM call feeds into the next. Ideal for structured, predictable pipelines — draft → review → reformat.
02 Classification
Routing
A classifier decides which specialized sub-agent or tool handles a request. Power customer support bots where queries route to billing, tech, or sales agents.
03 Concurrent
Parallelization
Multiple agents run simultaneously on sub-tasks, then results are aggregated. Sectioning splits large tasks; voting runs the same task N times for reliability.
04 Hierarchical
Orchestrator–Subagent
A manager LLM decomposes a goal and dispatches subtasks to specialist workers. The orchestrator synthesizes results — common in coding agents.
05 Iterative
Evaluator–Optimizer Loop
One agent generates output, another evaluates against criteria, and the generator refines based on feedback. Repeats until quality threshold is met.
06 Agentic
ReAct
Reason + Act. The agent interleaves reasoning steps with tool calls — think, act, observe, repeat. The backbone of most tool-using agents.
07 Deterministic
Plan-and-Execute
A planner LLM produces a full step-by-step plan upfront, then an executor works through it. More deterministic than ReAct; ideal for well-defined tasks.
08 Knowledge
RAG Pipeline
Retrieval-Augmented Generation — query → retrieve relevant chunks from a vector store → augment prompt → generate. Standard for enterprise knowledge Q&A.
09 Persistent
Memory-Augmented Agent
Agents maintain short-term, long-term, and episodic memory across sessions. Used in personal assistants and CRM-integrated agents that learn over time.
10 Consensus
Multi-Agent Debate / Critic
Multiple agents with different personas argue and critique each other's outputs. Improves factual accuracy and reduces hallucination on complex reasoning tasks.
Real-World Scenarios

Workflows in action

Each pattern maps directly to real business problems. Select a workflow to see how we apply it.

ScenarioHow it works
Legal contract draftingExtract key terms → draft clauses → check compliance → format final doc
Marketing campaignResearch audience → write copy → adapt for each channel (email, social, ad)
Medical report generationRaw lab values → interpret findings → write patient-friendly summary
ScenarioHow it works
Bank customer supportQuery classified → routed to fraud agent, loan agent, or account agent
HR helpdeskEmployee question → payroll bot, leave policy bot, or IT support bot
E-commerce chat"Where's my order?" → order tracking agent; "I want a refund" → returns agent
ScenarioHow it works
Due diligence on a company10 agents each analyze: financials, legal filings, news, patents, competitors — simultaneously
Multi-language product launchSame content translated into 12 languages in parallel, not sequentially
Insurance claimsPhotos, medical reports, and police reports analyzed by separate agents at once
ScenarioHow it works
Software feature developmentOrchestrator plans → subagents write code, write tests, update docs, review PRs
Market research reportOrchestrator defines sections → subagents research each section → orchestrator compiles
Travel planningOrchestrator takes your trip goal → subagents book flights, hotels, activities, visas
ScenarioHow it works
Ad copy A/B optimizationGenerator writes 5 variants → evaluator scores by persuasion criteria → generator refines weakest
Code quality gatesAgent writes function → evaluator checks correctness + edge cases → agent fixes until tests pass
Academic paper reviewDraft submitted → reviewer agent flags weak arguments → author agent revises → loop until accepted
ScenarioHow it works
Financial research assistant"What's Tesla's P/E vs competitors?" → searches web → reads earnings reports → calculates → answers
IT helpdesk bot"Server is down" → checks logs → pings server → reads error code → proposes fix
Shopping assistant"Best laptop under ₹80k for video editing" → searches stores → compares specs → recommends
ScenarioHow it works
Event managementPlan: venue, catering, invites, AV setup, contingency → execute each step in order
Onboarding new employeesFull checklist planned upfront → agent sends emails, creates accounts, schedules meetings
Data migration projectPlan all ETL steps → execute: extract, clean, validate, load, verify
ScenarioHow it works
Enterprise internal searchEmployee asks policy question → retrieves from HR docs/wikis → gives precise answer with source
Medical decision supportDoctor queries symptoms → retrieves matching case studies + drug references → surfaces recommendations
Legal research"Has this clause been challenged in court?" → searches case law database → summarizes precedents
ScenarioHow it works
Personal health coachRemembers your goals, past workouts, dietary preferences → advice that evolves over time
Sales CRM agentRemembers every call, email, objection per customer → preps reps before each meeting
Student tutoring botTracks concepts a student has struggled with → adjusts difficulty and examples over weeks
ScenarioHow it works
Investment decisionBull agent argues to buy, bear agent argues to sell → moderator agent synthesizes both views
Fake news detectionFact-checker + source-credibility + bias-detector agents independently evaluate → verdict by consensus
Architecture design reviewSecurity, performance, and cost agents each critique a system design → final recommendation emerges
Industries

Mapped to your domain

We identify the right workflow architecture for your industry — precisely matched, not one-size-fits-all.

🏦
Fintech / Banking
Routing RAG Pipeline Multi-Agent Debate
🏥
Healthcare
Prompt Chaining RAG Pipeline Memory-Augmented
⚙️
Software / Dev Tools
Orchestrator–Subagent Evaluator–Optimizer ReAct
⚖️
Legal
RAG Pipeline Parallelization Prompt Chaining
🛒
E-commerce
Routing ReAct Memory-Augmented
🏢
Enterprise / HR
Plan-and-Execute Routing RAG Pipeline
Our Approach

Built by engineers,
not prompt engineers

Real workflow architecture requires deep technical expertise. We bring both the AI knowledge and the engineering discipline.

01
Understand the problem
We start by mapping your business problem to the right workflow pattern — not the trendiest one, but the one that actually fits.
02
Architect the solution
We design the agent topology, tool integrations, memory strategy, and evaluation criteria before writing a single line of code.
03
Build and iterate
We engineer, test, and refine until the workflow meets real production standards — robust, observable, and maintainable.
Self-Serve Product

Start immediately
with Hellocaller

Not ready for a custom engagement? Our in-house self-serviceable product lets you experience AI agent workflows firsthand — built on the same patterns we deploy for enterprise.

Powered by real agent workflow patterns — not just a chatbot wrapper
Self-serviceable — configure, deploy, and iterate on your own timeline
Built by Chittaa Labs — the same team behind enterprise-grade implementations
Upgrade to custom workflows as your needs grow
Self-Serve · Available Now
hellocaller.io

Our in-house, self-serviceable AI workflow product. Built on the same agent patterns we implement for enterprise clients — available directly to you, with zero setup friction.

No engineering team required to get started
Production-ready agent workflows out of the box
Transparent, observable — see exactly what the agents are doing
Scales from solo founders to large enterprise teams

Ready to build workflows
that actually work?

Let's talk about your problem. We'll tell you honestly which workflow pattern fits — and how to build it right.