AI Solutions
Most businesses don't need "AI" as a headline feature — they need a specific repetitive task handled faster and more consistently. We build AI tools around that specific task.
The problem
Content that needs to be written every week, documents that need to be read and categorized by hand, or reports that take a person a day to compile from raw data — these are exactly the kind of tasks modern AI models are well-suited to handle, but only when the tool is built around your actual data and process, not a generic chatbot wrapper.
What we build
- AI-assisted content generation tools (e.g. SEO-oriented content pipelines)
- AI-powered document and form processing
- Generative AI data pipelines that turn raw data into structured reports
- AI assistants embedded into an existing website or internal tool
- Custom AI workflows connecting a model to your own data sources
Typical use cases
- A content pipeline that drafts SEO-oriented articles from a topic brief for human review before publishing
- A contact-form funnel that qualifies and routes incoming leads automatically
- A data pipeline that uses generative AI to turn raw analytics exports into a readable summary
- Document processing that extracts structured data from unstructured PDFs or forms
Why a custom approach can help
A generic AI chatbot bolted onto a website rarely earns its keep. The AI tools worth building are narrow and specific — connected to your real data, reviewed by a human where it matters, and measured against the actual task they replace. That's the standard we build to.
Frequently asked questions
Will AI replace our team?
No — and we wouldn't build it that way. AI accelerates specific, well-defined tasks (drafting, sorting, summarizing). Judgment calls, client relationships, and quality control stay with your team. Every AI-assisted output we build includes a human-review step before anything goes live.
How much does an AI business solution cost?
It depends heavily on scope — a single automated content workflow is a much smaller project than a custom data pipeline with multiple integrations. We scope this honestly during the discovery call rather than quoting a number blind.
Do you use our own data to train a model?
We typically don't fine-tune models — we use retrieval and prompt engineering against your existing data, which is faster to build, cheaper to run, and easier to update than a fine-tuned model.
Have a project that needs ai solutions?
Tell us about the problem you're solving — we'll tell you honestly whether this is the right fit.