What technology do you build with?

We use light, scalable infrastructure appropriate to the problem: serverless platforms, APIs, automation tools like Power Automate, and AI via Claude API where it adds value. We don't lock you into heavy infrastructure — you pay for what you use and the system scales with you.

Product Development

Bespoke AI systems built for your business

When you need more than a skill — customer-facing tools, automated workflows, system integrations — we build, deploy, and maintain the solution through our IDEAS Workflow.

Start the IDEAS process →

When You Need Product Development

Four signals that point to a bespoke build

Not every AI project needs custom development. These criteria help determine when a bespoke system is the right approach rather than an AI Enablement engagement.

👥 External users

The tool serves your customers, suppliers, or the public — not just your internal team. They can't be expected to hold Claude licences.

Example: A quoting tool on your website that customers use to get an instant estimate. The customer needs to use it without knowing what powers it.

⚡ System actions

The solution needs to write data, move files, sync systems, or trigger workflows across multiple platforms — not just analyse and advise.

Example: When a user clicks a button, the system saves renamed files to SharePoint, writes a timesheet entry, and files the email — all automatically.

🔗 No standalone value

The AI component only makes sense as part of a larger automated system. No user would invoke it directly — it's a component, not a tool.

Example: An invoice classification model that feeds an automated reconciliation pipeline. Useful as part of the pipeline, not on its own.

📊 Licence cost mismatch

The only Claude use case is this one function, and the seat count is high. A bespoke build with higher upfront cost may be more cost-effective over time.

Example: 50 staff needing a single classification function. At $25/user/month, that's $15,000/year in licences for one function. A bespoke build may make more sense.

The IDEAS Workflow

Four stages. Each one independently valuable.

You don't commit to the whole journey upfront. Each stage validates whether the next stage is worth pursuing. Stop at any point with a useful deliverable.

1Discover

IDEA Mapping

We map your business processes, identify where AI moves the needle, and produce a prioritised opportunity roadmap with feasibility and ROI estimates for each opportunity.

You get: Process audit, AI opportunity map, prioritised roadmap, ROI estimates, technical feasibility assessment, and a recommendation on which opportunity to prove first.

Typical timeline: 1–2 weeks

2Validate

Proof of Idea

A working prototype of the highest-priority opportunity. Real data, real workflow, real enough to validate the business case — before you invest in a full build.

You get: Working prototype, user feedback, validated (or invalidated) business case, refined requirements for full build.

Typical timeline: 2–3 weeks

3Build

Build Full Idea

The validated prototype becomes a production-ready system. Proper error handling, security, integrations, user interface, deployment, and documentation.

You get: Production system, deployment to your infrastructure, integration with your existing tools, user documentation, and handover training.

Typical timeline: 4–8 weeks

4Evolve

Maintain

Ongoing hosting, monitoring, updates, and improvement. The system stays current as your business evolves and as AI capabilities advance.

You get: Hosting and uptime management, monitoring and alerting, regular updates, feature improvements, and priority support.

Monthly retainer

What We Build

Common product development engagements

Every build is different, but these are the types of systems we deliver most often.

🤖

Managed AI Agents

Always-on AI systems that run autonomously — monitoring, processing, responding, and escalating without manual intervention. Deployed to your infrastructure with proper oversight and controls.

Learn about Managed AI Agents →

⚡

Process Automation

End-to-end workflow automation that moves data between systems, triggers actions, and handles the repetitive processes that consume your team's time. AI-powered where it adds value, conventional automation where it doesn't.

Learn about Process Automation →

Enablement + Product Development

Sometimes you need both

Some engagements span both services. The skill is built first as an Enablement engagement — delivering immediate value your team can use. The automation layer wraps it later as a separate Product Development project.

This phased approach means you get value quickly while the larger system is being built, and the skill becomes the intelligence layer inside the bespoke system via Claude API.

Worked example: Legal email filing

The need: Classify emails by matter, suggest fee items, file to SharePoint, log time entries.

Phase 1: AI Enablement — build a classification skill. Lawyers use it directly in Claude to classify emails during manual processing. Immediate value.

Phase 2: Product Development — build the Power Automate flow that saves files, writes time entries, and moves emails. The skill becomes the intelligence inside the automation.

Why Now

Your business can now afford to build its own software

Two years ago, a custom quoting tool or an automated client workflow meant a six-figure project, a dedicated dev team, and months of delivery. That was fine for enterprises with IT departments. For a 10–50 person business, it was simply out of reach.

AI has changed the economics fundamentally. McKinsey's research found that developers complete coding tasks up to twice as fast with AI tooling. The average cost of integrating an AI solution for an SME has dropped roughly 80% since 2023. And 62% of SMEs that adopted AI tools reported significant productivity improvements within six months.

The practical result: the quoting engine, the automated workflow, the customer-facing tool you always wanted but couldn't justify — it's now buildable, at your scale, on your budget. That's what Product Development is for.

Sources: McKinsey — Unleashing Developer Productivity with Generative AI, SmartDev — True Cost of Generative AI for SMEs

2×

Faster — developers complete tasks twice as fast with AI

80%

Drop in AI integration costs for SMEs since 2023

62%

Of SMEs see productivity gains within 6 months

23%

Average operational cost savings for SMEs using AI

Common Questions

Frequently asked questions

Everything you need to know about Product Development.

IDEAS is our four-stage process for building bespoke AI systems: IDEA Mapping (discovery and opportunity identification), Proof of Idea (working prototype), Build Full Idea (production system), and Maintain (ongoing support and improvement). Each stage is independently valuable and optional — you only proceed when the previous stage validates the opportunity.

AI Enablement delivers skills and plugins that run on Claude's platform — the intelligence itself. Product Development delivers bespoke systems: applications, automation flows, API integrations, and customer-facing tools that CyberCraft builds, deploys, and maintains. The system may use AI as a component, but the deliverable is the system itself. Learn about AI Enablement →

No. Each stage is independently valuable. Many clients start with IDEA Mapping to understand their opportunities and only proceed to Proof of Idea once the business case is clear. If the proof of concept doesn't validate the idea, you've invested weeks not months — and you move to the next opportunity on your roadmap.

We use light, scalable infrastructure appropriate to the problem: serverless platforms (AWS Lambda, Cloudflare Workers), automation tools (Power Automate, Make), APIs, and AI via Claude API where it adds value. We don't lock you into heavy infrastructure or proprietary platforms — systems are built to be maintainable and cost-effective at your scale.

That's exactly the point of the Proof of Idea stage — to validate quickly and cheaply before committing to a full build. If the prototype doesn't prove the business case, you move to the next opportunity on your roadmap having invested 2–3 weeks, not months. The IDEA Mapping stage typically identifies multiple opportunities, so there's always a next one to try.

IDEA Mapping takes 1–2 weeks. Proof of Idea takes 2–3 weeks. A full build typically takes 4–8 weeks depending on complexity. So from first conversation to production system, you're looking at roughly 2–3 months — with useful deliverables at each stage along the way.

Got a system in mind?

Tell us what you're trying to achieve. We'll tell you whether it's an Enablement engagement, a Product Development project, or both.