Service Overview
We build agentic AI workflows using the same orchestration framework that powers our WhatsApp chatbot (a 9-node agent graph), our internal FAQ system (a 6-node graph with human review), and our document processing pipeline. These aren't simple prompt chains — they're stateful, multi-step agent graphs where the AI reasons about what to do next, calls external tools, queries databases, and pauses at checkpoints for human approval when needed. State persists across sessions so agents pick up where they left off. When we build your workflow, it runs on patterns already proven in our products.
Key Benefits
Same orchestration running our WhatsApp and FAQ chatbots in production
Stateful workflows that resume after pauses and reboots
Tool use — agents call APIs, query databases, trigger actions
Human approval at any step you choose
Multi-agent systems for complex business processes
Full audit trail of every reasoning step and decision
Not prompt chains — real stateful agent graphs
Key Features & Capabilities
Our comprehensive solution includes these powerful features designed to maximize value and performance.
Agent graphs where the AI moves through defined nodes — each step produces a result, updates state, and decides what happens next. Not a single prompt, but a reasoning chain that adapts based on outcomes.
Agents call external tools at the right moment — query a database, send a message, create a record, process a document, trigger a webhook. The agent decides which tool to use based on the task at hand.
Configure points where the agent pauses and waits for human review, approval, or input before continuing. The human sees the reasoning so far and can approve, reject, or redirect.
Workflow state is saved at every step. If a session pauses for human review and resumes hours later, the agent picks up exactly where it left off with full context preserved.
Multiple specialized agents working together — one handles research, another makes decisions, a third executes actions. Each agent has its own role, tools, and reasoning within a shared workflow.
The same framework that runs our WhatsApp chatbot's 9-node graph and document processing pipeline. Production-tested with real message volumes, not a lab experiment.
Use Cases
Discover how organizations are leveraging this solution to address specific business challenges.
WhatsApp and messaging workflows
Multi-turn conversation agents that handle 24-hour messaging windows, template fallbacks, escalation to humans, and follow-up reminders. Our WhatsApp chatbot runs a 9-node graph in production today.
Document processing pipelines
Agents that receive documents, classify them, extract data, validate against rules, flag exceptions for review, and route results to downstream systems — all in a single stateful workflow.
Customer onboarding automation
Verify identities, validate documents, run compliance checks, provision accounts, and send communications — with human approval at the steps your compliance team requires.
Research and data synthesis
Agents that search sources, extract information, cross-reference findings, and compile reports — pausing for human review when confidence is low or stakes are high.
Order and transaction processing
Multi-step workflows that validate orders, check inventory, process payments, update systems, and handle exceptions — with escalation to humans for edge cases and high-value transactions.
Internal approval chains
Route requests through approval hierarchies where the agent gathers information, applies business rules, routes to the right approver, and tracks the chain until completion.
Implementation Process
Our structured approach ensures efficient delivery and exceptional results.
Workflow mapping and design
Map your existing process end-to-end — which steps are automatable, where human decisions are required, what tools and systems the agent needs to access, and what success looks like.
Agent graph and tool development
Design the agent graph (nodes, edges, state schema), build tool connectors for your APIs and databases, and configure human-in-the-loop checkpoints at the right decision points.
Testing against real scenarios
Test with your actual data and edge cases. Walk through normal flows, exception paths, and failure modes. Tune the agent's reasoning until decisions match your expectations.
Deployment and monitoring
Deploy with session persistence, execution logging, and performance monitoring. Track how the agent handles real tasks and iterate on the workflow as new edge cases emerge.
Frequently Asked Questions
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