Multi-step workflows
Agents break goals into actions across systems without brittle RPA scripts.
Qbatch · AI Agents
Agents that run the workflow — not just the chat.
Autonomous workflows that connect models to your tools and data. We design, evaluate, and ship agents your ops team can trust.
Runtime loop
STEP 1
Trigger
Ticket, form, or schedule
STEP 2
Plan
Agent selects next steps
STEP 3
Act
Calls tools & APIs
STEP 4
Verify
Eval + human gate
STEP 5
Complete
Write-back & notify
Capabilities
Built for production agent systems.
From a single ops agent to a supervised fleet — we optimize for correctness, cost, and auditability.
Tool & API connectors
Typed tool schemas for CRM, support, ERP, and internal microservices.
Grounded context
RAG and structured memory so agents act on your data, not guesses.
Guardrails built-in
Permissions, spend limits, and approval checkpoints for high-risk actions.
Orchestration patterns
Single agent, supervisor, or swarm — chosen for reliability, not hype.
Observability
Trace every step: prompts, tool calls, latency, cost, and outcomes.
Human-in-the-loop
Approve high-risk writes before they hit production systems.
Eval-first delivery
Golden datasets and regression suites before every release.
Cost envelopes
Token budgets and caching so agents stay economically viable.
AI agents FAQ
What is an AI agent vs a chatbot?+
Chatbots reply. Agents plan, call tools, update systems, and complete multi-step workflows with human approval where needed.
Which systems can agents connect to?+
CRMs, ticketing, ERPs, data warehouses, email, Slack, and custom APIs. We design tool interfaces with least-privilege access.
How do you keep agents reliable?+
Evaluation harnesses, step-level logging, retry policies, human-in-the-loop gates, and cost/latency budgets in production.