AI Agent Development & Workflow Automation
We build autonomous AI agents for fintech, payments, and Web3 — systems that plan, decide, and execute multi-step work across regulated, high-stakes environments. Then we put them into production with the monitoring, cost control, and governance enterprise teams actually need.
From a single task-automation agent to coordinated multi-agent systems: 14 years of software engineering, 350+ delivered projects, and deep blockchain and financial domain expertise behind every build.
Our AI agent development services
A traditional automation follows fixed rules. An AI agent is given a goal — not a script — and figures out the steps: it reasons, calls tools and APIs, retrieves context, and acts, adapting when conditions change. That difference is what lets agents handle the messy, long-running processes that rule-based automation has always struggled with. We help companies identify where agents create leverage, then build and ship them: starting with one or two high-value workflows, proving ROI, and expanding into orchestrated agent networks across the business.
01
Custom AI agents
Purpose-built agents designed from your workflows up — not configured templates. We write the reasoning logic, integrate the right models, and connect everything to your existing systems through APIs and secure connectors.
02
Multi-agent systems & orchestration
Coordinated agents that hand off work to each other — a research agent passes to a qualification agent, which routes to an execution agent — with governance checkpoints where humans need control. We handle the orchestration layer so the system stays reliable as it grows.
03
Workflow & business process automation
We sit agents on top of your current stack rather than replacing it: interpreting requests, applying business rules, and executing through existing interfaces and permissions. Most clients start with one or two high-volume processes to validate compatibility and governance before scaling.
04
RAG & knowledge agents
Agents grounded in your own data through retrieval-augmented generation — accurate answers and actions backed by your documents, knowledge bases, and live systems, not just model memory.
AI agents for fintech, crypto & Web3
Agents that touch sensitive data have to operate inside strict governance boundaries — we design for GDPR and the EU AI Act's transparency, human-oversight, and risk-management requirements from day one.
Compliance automation
agents that monitor regulatory registries, screen transactions, and surface risks continuously instead of in periodic batches.
KYC / AML automation
agents that orchestrate identity checks, escalate edge cases, and keep audit trails.
Smart contract & on-chain risk
agents that score contracts, domains, liquidity, and historical activity to flag fraud before a transaction executes.
Payments & banking operations
agents that automate reconciliation, dispute handling, and exception flows across payment infrastructure.
Case Studies
Wallet Guardian
Wallet Guardian is a Chrome browser extension powered by AI that scores token contracts in Ethereum and BSC networks. Designed to protect everyday users from scams, the system analyzes smart contracts, domain risks, exchange listings, liquidity metrics, and historical token activity to identify fraud before a transaction is executed. The product has helped users avoid millions in losses and is actively integrated into third-party systems via API.
How we build
We're a NestJS / TypeScript-first engineering team, building agent systems on production-grade foundations:
- Orchestration: LangChain, LangGraph, custom orchestration layers.
- Backend: NestJS, TypeScript, REST / event-driven APIs.
- Workflow tooling: n8n and custom pipelines for deterministic + LLM-hybrid flows.
- Retrieval: vector databases, RAG pipelines.
- Models: model-agnostic — frontier and open-weight LLMs selected per task and cost profile.
- Reliability: built-in tracing, token-cost tracking, and accuracy benchmarking from day one.
Backend
DevOps
AI agents development process
From pilot to production
Discovery & workflow audit
we map your processes and find where agents create real leverage (and where they don't).
Proof of concept
a working agent on one high-value workflow, with measurable success criteria.
Production build
integration, governance boundaries, monitoring, and cost controls.
Ongoing evaluation
agents improve through feedback loops, prompt tuning, and continuous benchmarking. We don't ship and disappear.
Ready to put AI agents to work?
Tell us the workflow you want to automate. On a free architecture consultation, we'll map the agent design, delivery timeline, and budget range — no commitment required.
FAQ
What is an AI agent?
An AI agent is software that autonomously plans, decides, and executes multi-step tasks. Unlike a simple prompt-and-response tool, you give it a goal rather than instructions for each step — it has reasoning, tool access, and memory to reach that goal on its own.
How is an AI agent different from traditional automation (RPA)?
Traditional automation and RPA follow fixed, predefined rules and break when conditions change. AI agents evaluate each situation against current data and context, make judgment calls, and adapt — which makes them suited to dynamic, long-running processes rather than only repetitive, identical tasks.
Should we build a custom AI agent or use an off-the-shelf platform?
Off-the-shelf platforms work well when you mainly need configuration on a stack you already run. Custom development earns its cost when agents must integrate with complex systems, reason across multiple data sources, or operate in regulated environments — common in fintech and Web3.
How much does AI agent development cost?
Cost depends on scope: a single-workflow proof of concept is a fraction of a coordinated multi-agent system with deep integrations and compliance requirements. We scope a fixed estimate after a discovery call — start with one workflow, prove ROI, then expand.
Can AI agents work with our existing systems?
Yes. Agents sit on top of your current platforms through APIs, orchestration layers, and secure connectors, using existing interfaces and permissions rather than replacing what you run.
Are AI agents safe for regulated industries?
They can be, with the right design. We build agents inside strict governance boundaries — defined permissions, human checkpoints, audit trails, and GDPR-compliant data handling aligned with EU AI Act requirements — which is essential for finance, payments, and compliance use cases.
The cost of solution development is determined by request and depends on the complexity of the project.
You can find out the standard order of calculation by sending an application.
Need AI Agent?
Get a free architecture consultation.
