Multi-Agent Orchestration
Planner, researcher, executor, and reviewer agents coordinating through typed message passing and shared memory.
ServicesAgentic AI
Agentic AI & Intelligent Systems
Autonomous software that does the work, not just answers questions.
operations-agentrun 4,182 · autonomousRUNNING
00:02Read 214 queued requestsSystems
00:09Resolved 197 · flagged 17MCP
00:14Checked own outputEval
00:16Escalated 2 items to a reviewer
92%Cleared unattended
100%Actions replayable
16sRun duration
Guardrails passedEvery step logged
What this is
Agentic AI is software that plans, acts across tools, checks its own output, and escalates to a person when it reaches the edge of its confidence.
Fintechy engineers this class of system for production, not demos. We build the agents, the integration layer that connects them to the systems you already run, and the guardrails and observability that make them dependable enough to run unattended. This is the practice where we engineer AI itself.
Governed tool access, logged and replayable
What We Build
Four capabilities, each engineered to run inside the systems and controls your organisation already operates under.
Autonomous Agent Platforms & Agentic Applications
We build agents that carry a task end to end: reading context, calling the right tools, and handing off to a human where judgment belongs. Every action is logged and replayable, so the system is inspectable rather than a black box.
Read more →MCP Server Development & AI Integration Architecture
We develop Model Context Protocol servers and the integration architecture that connects agents to your ERP, CRM, and data platforms in a governed, maintainable way. Most firms are not building this yet. We are.
Read more →AI-Native Workflow Orchestration
We orchestrate multi-step workflows that combine model reasoning, tool calls, and deterministic steps into one reliable system, with a human in the loop wherever the stakes require it.
Read more →Applied AI Engineering
We apply AI to a specific, high-value problem and engineer around it: evaluation suites, guardrails, prompt-injection defenses, and trace-level observability, so the result holds up under real use.
Read more →The engineering underneath an agent that runs unattended: coordination, tool access, controls, memory, evaluation, and economics.
Tool & API Integration
Secure tool calling over Model Context Protocol (MCP), REST, GraphQL, and enterprise event buses.
Human-in-the-Loop Controls
Approval gates, confidence thresholds, and escalation workflows integrated with Slack, Teams, and email.
Memory & Context
Long-term vector memory, session memory, and structured knowledge graphs for persistent agent reasoning.
Evaluation & Guardrails
Continuous offline eval suites, prompt injection defenses, output validators, and trace-level observability.
Cost & Latency Optimization
Model routing, caching, batched tool calls, and SLO-driven architecture for predictable economics.
How We Work
We start with the one or two workflows where an agent earns its place, design the agent topology and escalation paths, then build with evaluation and logging from the first commit. You get a system your team can see into and trust, delivered in weeks, not quarters.
Pick the workflow
The one or two places where an agent earns its place.
Design the topology
Agent boundaries, tool access, and escalation paths.
Build with evals
Evaluation and logging from the first commit.
Explore More
Have a workflow an agent could run. Let's look at it together.
Book a call →calendly.com/fintechy/30min
What we cover
The workflow, step by step
Where an agent fits, and where it doesn't
What a first build would take