We build multi-agent systems that triage, route, decide, and execute across your existing tools — without a human in the loop. Not chatbots. Not copilots. Autonomous agents that do the work.
// 10+ years · Fortune 10 production systems · multi-agent architectures
Manual ticket triage. Copy-pasting between systems. Routing requests to the right person. Running the same report every Monday. These aren't hard problems — they're repetitive decisions your team makes on autopilot. We replace the autopilot with actual agents.
Most AI tools hand you a chatbot that still needs babysitting. We architect multi-agent systems on production-grade frameworks — agents that ingest, classify, decide, route, and execute across your existing stack. They run continuously. They don't forget. They don't get tired.
// EXAMPLE
A 200-person operations team manually triages 400+ support tickets per day. Each ticket takes 3-5 minutes to read, classify, and route. That's 25+ hours of human time daily — on decisions an agent makes in seconds. After deployment: under 15 minutes of human review per day. The rest is autonomous.
Multi-agent systems that read incoming requests, classify priority, extract entities, and route to the right team — replacing hours of manual sorting with seconds of autonomous processing.
→ Hours of sorting reduced to seconds
Agent pipelines that handle approvals, escalations, status updates, and cross-system data sync. Built on LangGraph with state management that handles edge cases your scripts can't.
→ Zero manual handoffs between systems
Retrieval-augmented agents grounded in your internal documents, SOPs, and knowledge bases. Answers come from your data with source citations — not hallucinations.
→ Answers grounded in your data, not guesses
We map your current workflows, identify where human time is wasted on automatable decisions, and scope the highest-impact agent system. You get a clear architecture doc before any code is written.
We architect your multi-agent system, integrate with your existing tools, and run it in shadow mode alongside your team. The agents process real data but don't take action — so you validate accuracy before going live.
Your agents go live. We monitor performance, tune decision logic, and expand scope as your team builds confidence. Ongoing support included — agent systems aren't set-and-forget.
10+ years of software engineering across enterprise-scale systems, with deep focus on agentic AI, fleet automation, and LLM-integrated tooling. Background includes multi-agent ticket analysis systems, RAG pipelines, and autonomous workflow agents deployed at Fortune 10 scale.
Refiney.io was founded to bring production-grade agentic AI — the kind that runs reliably across thousands of endpoints — to companies that need agents which work, not demos that impress.
Most engagements start with a 2-week operations audit, followed by a 4-6 week build phase where we architect and deploy the agent system. After launch, we provide ongoing monitoring and optimization. Typical first engagements run 2-3 months end to end.
We work with whatever your team already uses — Jira, Salesforce, Slack, HubSpot, Zendesk, Google Workspace, internal APIs. The agent systems are built to plug into your existing stack, not replace it.
Every system starts in shadow mode — agents process real data but don't take action until accuracy is validated. Once live, confidence thresholds and human escalation paths ensure that edge cases get routed to your team, not buried. You stay in control.
We're taking on 2-3 companies for Q2. Let's talk about what's eating your team's time.
Book a Strategy Call →30-minute call · no obligation · team@refiney.io