Make your business usable by AI agents, safely.
Customers and teams increasingly work through AI assistants like Claude and ChatGPT. We make your store, ERP, accounting, booking, and internal systems usable by those agents through secure MCP connectors, so they can order, pay, book, and check status, with scoped access, audit logs, and human approval built in.
Why most AI projects stall
Demo-to-production gap
A prompt that works in a notebook breaks on real data. Without evaluations, nobody knows if a change made things better or worse.
Trust in regulated settings
Fintech and commerce teams need explanations, audit trails, and human review before AI touches customers or money.
Unpredictable cost & latency
Token spend and response times grow with usage. Architecture choices made early decide whether a feature is affordable at scale.
Data stuck in silos
The most valuable context sits in documents, tickets, and internal databases that an off-the-shelf chatbot can't reach safely.
How we help
From strategy and solution design to launch and continuous improvement.
- MCP servers for your APIs & data
- Tool-calling agents & integrations
- LLM-powered product features
- Retrieval (RAG) over your documents & data
- AI agents for internal operations
- Document & KYC data extraction
- Support & operations copilots
- Product search & recommendations
- Evaluation suites & guardrails
- Cost, latency & privacy engineering
How we make AI safe to adopt
Start with the workflow
We pick tasks where AI removes real hours, like alert triage, document review, or catalog enrichment, before choosing a model.
Measure before and after
Every feature ships with an evaluation set, so quality is a number you can track rather than a feeling.
Humans approve what matters
Anything touching money, compliance, or customers goes through review queues with full audit trails.
Your data stays yours
We design for least-privilege access, redaction, and providers whose terms fit your compliance posture.
Agent-ready connectors
Secure integrations that let Claude, ChatGPT, and other AI agents work with real business systems.
MCP Gateway
A hosted gateway that sits in front of every MCP connector we build: OAuth sign-in, per-tool scopes, rate limits, human approval for risky actions, and a complete audit log of every agent request.
View projectWooCommerce Agent Connector
An MCP connector that lets Claude and ChatGPT search a WooCommerce catalog, check stock and delivery, build a cart, and hand the customer a secure checkout link, with no store rebuild.
View projectERP Agent Connector
An MCP connector for Odoo that lets operations teams ask Claude about stock, open orders, and deliveries, and draft sales orders and purchase requests that go through the ERP's own approvals.
View projectAccounting Agent Connector
An MCP connector for Xero that lets finance teams ask an AI assistant who owes what, which invoices are overdue, and what cash looks like, and draft invoices and reminders for approval.
View projectBooking Agent Connector
An MCP connector that lets AI assistants check real availability, book, reschedule, and cancel appointments in a business's scheduling system, with confirmations sent by the business itself.
View projectBanking Ops MCP
An MCP server for banking operations teams: look up balances, trace payments across ACH, wire, RTP, and FedNow, review open fraud and compliance alerts, and request account holds that require dual approval.
View projectOur thinking on AI
Where AI actually pays off in fintech and e-commerce (and where it doesn't yet)
The best AI projects remove hours from a known workflow. The worst try to automate judgment that regulators and customers expect a human to own.
Shipping an LLM feature to production: an engineering checklist
Getting a prototype to work takes a day. Getting it to work reliably, affordably, and safely for real users takes engineering. This is the checklist we use.