Agentic AI
Build agents that
work in production
The complete platform for building, deploying, and operating autonomous AI agents with full observability and control.
Why build agents on Devscale
Move beyond prototypes. Ship agents that operate reliably at production scale.
Closed-Loop Systems
Build agents that perceive, reason, act, and observe — operating autonomously in production with built-in feedback loops and self-correction.
Full Observability
Trace every agent decision, tool call, and reasoning step. Monitor token usage, latency, and success rates across your entire agent fleet.
Iterative Improvement
Log every interaction, evaluate outcomes, and fine-tune agent behavior over time. Production data feeds directly into model improvement cycles.
Production-Ready
Enterprise-grade guardrails, rate limiting, retry logic, and fallback mechanisms. Deploy agents with confidence at any scale.
Agent architecture
A closed-loop system designed for autonomous operation with full human oversight.
Input & Intent
Receive user queries via API, chat, or event streams. Parse intent, extract entities, and route to appropriate agent workflows.
Planning & Reasoning
LLM-powered reasoning engine decomposes tasks into sub-goals, selects tools, and generates execution plans with confidence scoring.
Execution & Tool Use
Agents invoke tools, APIs, and services with sandboxed execution, retry logic, and automatic error recovery.
Observation & Feedback
Every step is logged and traced. Real-time dashboards surface latency, cost, success rates, and reasoning quality metrics.
Agents for every use case
From simple tool-calling to complex multi-agent orchestration.
Autonomous Agents
Deploy long-running agents that independently plan, execute multi-step tasks, and adapt to new information — operating 24/7 without human intervention.
Tool-Use
Connect agents to APIs, databases, code interpreters, and external services. Function calling, RAG pipelines, and structured output built in.
Multi-Step Reasoning
Chain complex reasoning tasks across multiple models and tools. Decompose problems, verify intermediate results, and synthesize final answers.
“We built an autonomous data pipeline agent that previously required a team of 5 engineers. It now handles schema migrations, data quality checks, and incident response — running 24/7 with full observability. Our team focuses on building new capabilities instead.”
Priya Nair
Director of Engineering, DataForge
Frequently asked questions
Ready to ship production agents?
Build, deploy, and operate autonomous AI agents with enterprise-grade observability and control.