Stop buying
platforms.
Delegate the work.
We build AI agents that handle specific tasks inside your existing operations — no new software licence, no vendor lock-in. If the agent doesn't work, neither do we.
Find the right starting point
Leads fall through because no one gets to them in time
Your sales team spends 40 minutes a day qualifying inbound requests, scheduling calls, and updating the CRM. By the time someone follows up, the lead has moved on or gone cold. The bottleneck isn't motivation — it's the mechanical work between "enquiry received" and "meeting booked."
What an agent handles
- Reads and classifies inbound enquiries within seconds of receipt
- Qualifies against your defined criteria and scores urgency
- Books a slot in the right rep's calendar without human touch
- Writes the first follow-up email in your voice
- Logs everything to your CRM automatically
Someone spends Friday afternoon pulling numbers together
Weekly or monthly reports require someone to log into four systems, copy figures into a spreadsheet, write a summary, and send it to seven people. It takes 3–4 hours, it's error-prone, and the person doing it finds it soul-crushing. The report itself is valuable — the assembly isn't.
What an agent handles
- Pulls data from your sources on a schedule you define
- Normalises and aggregates across formats
- Generates the narrative summary with variance commentary
- Distributes to the right recipients via email or Slack
- Archives a version-controlled copy automatically
Your support team answers the same 12 questions every day
Your first-line team handles hundreds of requests monthly. A significant portion — status updates, basic how-tos, account information — could be answered without a human in the loop. But generic chatbots give generic answers, and your clients notice.
What an agent handles
- Understands your specific product, policies, and tone
- Resolves known patterns without human handoff
- Escalates edge cases with a full context summary
- Logs resolved and escalated tickets separately
- Learns from corrections over time
Contracts and documents sit in email waiting for someone to read them
Incoming contracts, supplier invoices, compliance documents, or client briefs need to be read, classified, extracted, and filed before any decision can be made. Someone is doing this manually — usually a capable person who could be doing something more difficult.
What an agent handles
- Ingests documents from email, uploads, or shared drives
- Extracts key fields — dates, values, parties, obligations
- Classifies document type and routes accordingly
- Flags anomalies or missing required fields
- Files to the correct location with structured metadata
An agent running inside your stack
We don't plug in a third-party widget. We build an agent that sits inside your existing tools — your email, your CRM, your database — and handles a defined task end to end.
You see what it does. You own the logic. If it makes a mistake, you can inspect why — and we're still accountable.
Four types of engagement
Each one starts with mapping the process before we write a line of code.
Process Audit
We map a specific workflow end to end, identify where AI can take over without risk, and produce a written assessment. No commitment to build required.
Starting pointAgent Build
We design, develop, and test a custom agent for one specific process. Includes integration with your existing tools, documentation, and a 30-day accountability period post-launch.
Core offeringTeam Integration
Your team learns to work alongside the agent — what to trust, when to override, how to correct it. Delivered as structured half-day sessions, not generic AI training.
Alongside buildMaintenance & Iteration
Agents need tuning as your process evolves. We offer a quarterly review and adjustment cycle — monitoring performance, catching edge cases, and updating logic when something changes.
OngoingQuestions worth asking before you reach out
No. Most of our clients come with existing tools — an email server, a CRM, a database — and no AI layer. We build the agent to work with what's already there. You don't need to replace anything to get started.
Every agent we build has an audit log and a defined escalation path. Errors are visible, traceable, and correctable. We stay accountable for the first 30 days post-launch and provide a documented response within 24 hours of any reported failure. We don't disappear after delivery.
The build is a project fee. Maintenance is an optional monthly retainer. There's no platform subscription — you're not paying us to use software. You're paying us to build something that works for your specific process, and then optionally to keep it tuned.
A working prototype is usually ready within two weeks. Full production deployment — with your integrations, testing, and team sessions — takes four to six weeks depending on the complexity of the process and how quickly we can get access to your systems.
If your process isn't documented and your team disagrees about how it works, we'll spend most of our time on process design rather than agent development — which isn't where we add the most value. We also don't work well with companies that need the agent built in under a week, or that want a generic chatbot without a specific task. We're better suited to operational problems that already have a clear shape.
Notes on building with AI agents
What an AI agent actually is — and isn't
The word "agent" is used for everything from a chatbot to a full autonomous system. Here's a precise definition and a framework for deciding which type fits your use case.
Why we audit the process before writing any code
Every failed AI project we've seen started with a solution before anyone had mapped the problem. Here's the audit framework we use on day one of every engagement.
The 14-day path from process to working agent
A transparent look at what happens in our first two weeks — what we need from you, what we produce, and the decisions we make along the way.
Ready to hand something off?
Tell us which process you'd like to remove from your team's plate. We'll respond with a candid assessment of whether an agent is the right tool — and if it is, what building one would look like.
Start with a process description