AI Agents & Automation
AI agent development company & AI automation agency for business workflows—deterministic tool calling, stateful memory & human-in-the-loop gates.
Direct Answer Summary
Rohini designs and deploys production AI agents and workflow automation systems that execute real business tasks—qualifying leads, triaging support tickets, syncing CRM/ERP records, and generating structured reports. Unlike brittle prompt wrappers, our agents use strict JSON-schema tool contracts, idempotent retries, persistent state, and human-in-the-loop approval gates.
Execution
Tool-Calling
Strict JSON Schema validation for every API & DB action.
Reliability
Idempotent + DLQ
Bounded retries, circuit breakers, and dead-letter queues.
Integrations
CRM / WhatsApp
Connects to HubSpot, Zoho, Slack, Email, PostgreSQL, and webhooks.
Starting From
₹40,000
Custom workflow agents with observability & evals.
Technical Architecture Breakdown
1. Deterministic State Machine & ReAct Loop
Bounded reasoning steps with explicit state transitions prevent infinite agent loops and runaway token spend.
2. Sandboxed Tool Execution & Idempotency
Every external write (sending an email, updating a CRM deal, issuing a refund) uses idempotency keys and strict RBAC scopes.
3. Short-Term & Long-Term Memory
Redis stores active session scratchpads while PostgreSQL/pgvector persists structured user preferences and episodic interaction history.
4. Human-in-the-Loop & Cost Telemetry
High-impact actions pause for one-click Slack/dashboard approval, with per-tenant token tracking and trace logging.
Production Tech Stack Matrix
| Layer | Technologies | Architectural Rationale | Production Guarantee |
|---|---|---|---|
| Orchestration | LangGraph / Custom State Machines, Node.js / Python | Deterministic branching & resumable checkpoints | Bounded max-step execution |
| Models & Routing | OpenAI, Anthropic Claude, Gemini, Grok | Task-routed models (fast/cheap vs deep reasoning) | Automatic provider fallback |
| Memory & Queues | Redis, PostgreSQL + pgvector, BullMQ / Kafka | Durable async job execution & semantic recall | Zero lost webhook events |
| Observability | OpenTelemetry, Structured Trace Logs, Evals | Full visibility into tool inputs, latency & cost | Reproducible failure replay |
Commercial Use-Case Matrix
| Scenario | Core Requirement | Delivered System | Outcome |
|---|---|---|---|
| 24/7 Lead Qualification | Engage web/WhatsApp leads, book calls, sync CRM | Conversational agent + calendar/CRM tools | < 5s first response time |
| Support Ticket Triage | Classify, draft replies, escalate billing bugs | Classifier + RAG drafts + human approval | 60% faster ticket resolution |
| Back-Office Invoice & Ops | Extract PDFs, validate POs, update ERP | Structured extraction agent + audit queue | 90% less manual data entry |
Related Engineering & Architecture Guides
Frequently Asked Questions
How do you prevent AI agents from hallucinating or taking wrong actions?
We enforce strict JSON Schema tool contracts, read-only vs write permission tiers, and human-in-the-loop approval for any high-risk mutation.
Can agents integrate with our existing WhatsApp, CRM, or internal database?
Yes. We build secure API adapters with scoped credentials and rate limits for any internal or third-party system.
How are LLM API costs controlled in production?
We use model routing (lightweight models for classification, frontier models only for synthesis), semantic caching, and hard per-session token budgets.
Tailored Project Scoping
Scope your AI Agents & Automation project with Rohini
Share your requirements and our engineers will respond within 24 hours with architecture notes, timeline, and a practical estimate.