AI AGENTS

AI Agent Development Company
Autonomous agents that actually work in production.

We build AI agents that execute complex, multi-step workflows reliably — with guardrails, observability, and the engineering rigor that production demands.

WHAT WE BUILD

From single agents to full orchestration.

Task-Specific Agents

Single-purpose agents with deep tool integration for one critical workflow. Highly reliable, fast to deploy, easy to monitor.

Multi-Agent Pipelines

Specialized agents coordinating on complex tasks — researcher, analyst, writer, reviewer working in sequence or parallel.

Orchestration Systems

Central orchestrator routing tasks to the right agents with state management, error recovery, and human escalation.

Human-in-the-Loop

Agents that know when to ask for help. Confidence thresholds, approval gates, and escalation paths baked into the architecture.

Tool-Use Agents

Agents with real-world capabilities: web search, code execution, database queries, API calls, file manipulation, email, calendar.

Agent Monitoring

Full observability into every agent run — tool calls, reasoning traces, token usage, success rates, and failure analysis.

AGENT STACK

The tools behind production agents.

Orchestration Frameworks

LangGraphCrewAIAutoGenLangChain

Foundation Models

GPT-4oClaude 3.5 SonnetGemini 1.5 ProLLaMA 3

Tool Integrations

BrowsingCode ExecAPIsDatabasesEmailCalendar

Observability

LangSmithHeliconeArize PhoenixW&B Traces

Memory & State

RedisPostgreSQLPineconeQdrant

Infrastructure

FastAPICeleryDockerKubernetesAWSGCP

CASE STUDY

Campaigns drafted by AI, approved by people.

CASE STUDY · AI SAAS PLATFORM

Feedlio: AI Social Media SaaS

IN-HOUSE PRODUCT

12
Networks live
3
MCP directories listed
Daily
Used for our own marketing

Our own AI platform plans, writes and publishes content to 12 networks. An AI Campaign Builder drafts whole campaigns for human approval, and a hosted MCP server lets assistants like Claude and ChatGPT schedule posts directly.

Stack

Next.jsTypeScriptMongoDBModel Context Protocol

FAQ

Common agent questions.

Traditional automation follows fixed rules for known inputs. AI agents reason about tasks, choose tools dynamically, handle unexpected situations, and can complete multi-step workflows that require judgment — not just if/then logic.
Guardrails at every tool call, structured output validation, retry logic with exponential backoff, human-in-the-loop fallbacks for low-confidence decisions, and full audit trails. Reliability is an engineering problem, not a prompt engineering problem.
APIs, databases, file systems, web browsers, CRM systems, email, Slack, Notion, custom business tools — any system with a programmatic interface. We build custom tool wrappers where needed.
A single-purpose agent with 3–5 tools typically takes 4–6 weeks from discovery to production. Multi-agent orchestration systems with human-in-the-loop controls typically run 8–12 weeks.

BUILD YOUR AGENT

Automate your most complex workflows.

Tell us what you want to automate. We'll design the agent architecture and give you a fixed quote.

No commitment — a technical deep dive with our lead engineers · Trusted by 65+ teams since 2016