Make your systems
agent-ready.
Legacy systems and APIs you can't rewrite? We turn them into governed tools that AI agents can safely use, exposed through an MCP gateway, running on cloud or local models, and delivered by forward deployed engineers who work inside your team.
Claude · Copilot · Internal agents
- REST APIs
- SOAP services
- Databases
- Mainframe / files
- Local open-weight
- Private cloud
- Frontier APIs
The problems we get called in for
Agentic AI is easy to demo and hard to put in production. These are the blockers we help organisations get past.
“We want to use agentic AI, but we don't know where to start.”
A short readiness assessment: we inventory your systems and APIs, pick the first workflow worth automating, and give you a fixed-price plan.
“We have hundreds of APIs, but none of them were designed for agents.”
We turn them into curated, task-level MCP tools with clear schemas and descriptions, not a raw dump of every endpoint.
“Security won't let an LLM anywhere near production.”
An MCP gateway with identity-aware access, policy checks, human approval for writes, rate limits, and a full audit trail.
“Our data can't leave the building.”
Open-weight models deployed on your own hardware or private cloud, connected to private retrieval and the same governed tools.
“Our core system is SOAP, a mainframe, or a database nobody wants to touch.”
A thin adapter layer that exposes what agents need, reads first and from replicas where possible, without destabilising the system underneath.
“Every team is building its own AI integration.”
One tool catalogue behind one gateway. Build each integration once and reuse it across Claude, Copilot, and your internal agents.
“We built a proof-of-concept. It never made it to production.”
Forward deployed engineers who work inside your environment and ship it: CI/CD, evals, monitoring, runbooks, and handover.
“We have no idea what the agent actually did.”
Tracing and audit-grade logging of every tool call: who it acted for, what it sent, what came back, and who approved it.
“Our token bill keeps climbing and we can't see why.”
Smaller tool responses, caching, and routing routine steps to cheaper local models, with frontier models only where they earn it.
From existing systems to governed agents.
Everything between “we have APIs” and “agents are safely doing real work in production.”
Agentic AI Readiness Assessment
Want to use agentic AI but don't know where to start? We map your systems, APIs, and constraints, then pick the first workflow worth automating.
Learn moreAPI-to-MCP Tool Conversion
Your APIs were built for developers, not agents. We turn them into well-designed, governed tools any agent can use through the Model Context Protocol.
Learn moreMCP Gateway & AI Governance
One governed front door for every agent. Scoped auth, policy checks, human approvals, rate limits, and an audit trail of every tool call.
Learn moreLocal & Private Models
When data can't leave your network, the model comes to you. Open-weight models on your hardware or private cloud, wired into the same tools and gateway.
Learn moreLegacy System Integration
SOAP services, mainframes, old databases, file drops. We build the adapter layer that makes legacy systems usable by modern agents without rewriting them.
Learn moreForward Deployed Engineering
Engineers who embed with your team, inside your environment, and ship agentic systems to production, then hand over something your team can run.
Learn moreWhat this looks like in practice
A completed agentic automation project, plus two illustrative blueprints showing how we approach agent-ready integration for legacy and data-sensitive environments.
The Challenge
A Brisbane-based charity with a single employee was losing hours every week to administrative work — grant reporting, social media, donor emails, and inbox management — leaving less time for the relief work that mattered most.
The Outcome
4–5 hours/week of administrative time saved for a one-person team. A clear, actionable AI roadmap delivered within a single engagement.
Zero new platforms. Zero vendor lock-in. Built on tools they already owned.
AI Workflows Delivered
- Quarterly Impact Synthesiser — Pulls program outcomes and auto-drafts a 2-page Impact Summary every 90 days for funders
- Social Content Creator — Generates platform-optimised posts for Instagram, Facebook, and LinkedIn from existing reports
- Grant Prospector — Scans the web for funding opportunities aligned to the org's mission and tracks them in a live Google Sheet
- Smart Triage Inbox — Summarises threads, drafts routine replies, and flags complex requests for human attention
- Content Calendar Sentry — Monitors the publishing schedule and alerts when a post date approaches without a draft
Not sure if your use case fits? Let's find out in 30 minutes.
Get in TouchWhat an engagement looks like
From first conversation to agents doing real work in production, without a six-month strategy phase.
Discovery Call
A 30-minute technical conversation about your systems, constraints, and what you want agents to do. No sales fluff.
Readiness Assessment
We inventory your APIs and legacy systems, review security and data constraints, and pick the first workflow worth automating.
Scoped Proposal
Within 5 days, you receive a fixed-price proposal: the tools, the gateway controls, the model choice, and the timeline.
Forward Deployed Build
Our engineers embed with your team, ship to production in your environment, and hand over docs, evals, and runbooks.
Engineering-Led. Governance First.
We don't deliver slide decks; we deliver software. We work as forward deployed engineers inside your environment, connecting agents to the systems you already run, safely and auditably.
Our engineering background in Defence and banking systems means we treat security, auditability, and legacy constraints as design inputs, not afterthoughts. We have hands-on experience running open-weight models locally, building MCP tools, and putting governance controls in front of production systems.
Cloud or Local
The right model for your data rules
Patent Pending
Autonomous systems governance
Cloud Platforms
AWS Bedrock, Azure OpenAI, and frontier model APIs, with hybrid cloud/local routing.
Local Models
Open-weight models served on your own hardware with vLLM or Ollama, plus private RAG.
MCP Tools
Turning existing APIs into task-level tools agents can use reliably.
Legacy Systems
SOAP services, mainframes, old databases, and file-based integrations.
Agent Orchestration
Multi-step agents with evals, tracing, and human-in-the-loop approvals.
Governance
MCP gateways with scoped auth, policy checks, and audit trails.
Let's find your first agent-ready workflow.
A 30-minute call to talk through your systems, your constraints, and where agents could do real work.
No hard sell. After the call you'll know where to start, what it would involve, and roughly what it would cost.
Readiness assessments start from $1,500. Fixed-price implementations from $8,000.