Add AI to the software you already run - honestly scoped
Document intelligence, workflow automation and AI agents wired into applications that already work, with human checkpoints at the decisions that matter. If AI isn't the right fit for what you're trying to do, we'll say so.
In short
- Two entry points: AI for Existing Applications - document intelligence and workflow automation added to what's already running - and AI Automation, for repetitive work like invoice processing and document review.
- AI Agents means multi-step AI assistance with human checkpoints at the decisions that matter, not fully autonomous decision-making - built into the two services above as needed.
- Most of the work is adding AI to software a business already runs, not building a new AI product from scratch.
- We'll tell a client when AI would add cost and risk without a real payoff, rather than sell it anyway.
- Real proof: Karneyium, with OpenAI's models built into a live product alongside React, .NET Core, PostgreSQL and ArcGIS.
Where Does an AI Engagement Usually Start?
AI for Existing Applications
Add AI capabilities to the software your business already uses. Integrate document intelligence and workflow automation into what's already running.
Learn MoreAI Automation / AI-Powered Applications
Automate invoice processing, document review, and other repetitive work with AI wired into the systems you already run.
Learn MoreWhat Else Is Part of This Work?
AI Agents
Multi-step AI assistance with human checkpoints at the decisions that matter - not fully autonomous decision-making - built into the two services above as needed.
Frequently asked questions
Do you only add AI to new applications, or to existing ones too?
Mostly existing ones. Most of what we do is adding AI capabilities to software a business is already running, not building a new AI product from scratch.
Will you tell us if AI isn't the right fit?
Yes. Part of scoping this honestly is telling a client when AI would add cost and risk without a real payoff - we'd rather say that upfront than sell it anyway.
What does a 'human checkpoint' mean in an AI workflow you build?
A point in the process where a person reviews or approves the AI's output before it acts on something that matters - AI does the multi-step legwork, a person still makes the call.
What AI providers do you work with?
We've shipped production work on OpenAI's models - see the Karneyium case study below for an example built into a live product.
Considering AI for something specific?
Tell us the use case. We'll give you an honest read on whether AI is the right tool for it.
Discuss Your AI Use Case