.svg){kind=icon}
AI Agents That Work in Production, Not Just in Demos
We build autonomous agents that handle multi-step business workflows — processing documents, managing orders, automating compliance — with the guardrails and reliability that production environments demand.
Why We Build Agents Differently
The gap between a working demo and a production agent is where most AI projects stall. We close that gap because we build and operate agents for our own teams first.
Demo Agent
Agent works perfectly with well-structured test data. Demos impressively. Stakeholders approve the concept.
Single path from input to output. No branching logic for exceptions. No recovery when something unexpected happens.
System prompts tuned for ideal inputs. No handling for ambiguous, incomplete, or adversarial user messages.
Token usage unchecked. No limits on API calls. Fine in a demo, unsustainable at scale with real traffic.
When the agent fails, it fails quietly. No escalation path. No monitoring. No way to know it broke until a user complains.
Production Agent (How We Build)
Every input validated before processing. Guardrails prevent hallucination, scope drift, and unsafe outputs. Built from real-world edge cases.
Agents handle exceptions, retry with backoff, and degrade gracefully. When they cannot complete a task, they escalate — not fail silently.
Transparent escalation paths when confidence is low. Full context preserved so the human picks up where the agent left off.
Token budgets, API rate limits, and cost monitoring built in from day one. Production-ready means financially sustainable at scale.
Every agent action is logged and monitored. Performance tracked, failures surfaced, and the agent improves based on real production data.
What We Deliver
Workflow Automation Agents
Agents that execute multi-step processes across systems - triggering from events, pulling data, processing it, updating records, and notifying stakeholders.
Document Intelligence Agents
Extract, classify, validate, and route information from documents - invoices, contracts, compliance filings - into structured, system-ready output.
Conversational Commerce Agents
AI agents on WhatsApp, web, and voice that take orders, confirm transactions, check availability, and escalate to humans when needed.
Multi-Agent Systems
Workflows where specialized agents collaborate - one researches, another analyzes, a third drafts, a supervisor validates. For tasks too complex for a single agent.
Internal Operations Agents
Agents for your team: meeting summarizers, sales prep assistants, reporting automation, knowledge base search. Built from patterns we run internally.
Agent Monitoring & Optimization
Post-deployment tracking of accuracy, cost, latency, and satisfaction. Continuous improvement loops that refine agent behavior from real usage data.
Technology Stack
Our Work
AI Demo / Cross-Industry
Built an AI agent that processes unstructured documents with 85% extraction accuracy
Processes invoices, contracts, and reports with intelligent field
extraction and confidence scoring
Validates extracted data against configurable business rules
before downstream push
Handles multiple document formats (PDF, scanned images, emails)
with OCR integration
Provides audit trail and exception queue for human review of
low-confidence extractions
85%
Extraction Accuracy
70%
Faster Document Processing
90%
Reduction in Manual Review
Deployed a WhatsApp agent that processes B2B orders 60% faster across 3 languages
Processes orders via text and voice messages in English, Hindi,
and Spanish
Confirms line items, quantities, and pricing with the buyer
before submission
Checks real-time inventory availability and suggests alternatives
for out-of-stock items
Routes confirmed orders to fulfillment and sends delivery tracking
updates
60%
Faster Order Processing
40%
Reduction in Order Errors
3
Languages Supported
Automated 75% of support ticket classification with AI-driven triage and routing
Monitors incoming tickets across email, chat, and web form
channels in real time
Classifies tickets by category, urgency, and complexity using
trained language models
Assigns priority scores and routes to the correct team based on
skill matching
Learns from resolution patterns to continuously improve
classification accuracy
75%
Automated Classification
50%
Faster Resolution Time
30%
Fewer Misrouted Tickets
Follow Us
.svg)
