AI That Makes Operational Decisions — Not Chatbots
Most “AI features” are a chat box bolted onto an existing product. We build AI into the decisions that actually bottleneck a business: what to charge, who to assign, whether a schedule is executable, what a document says, and what your data is telling you.
A production AI pipeline, end to end
Our clearest proof point is a system we built and run ourselves: an AI content pipeline that takes a single campaign keyword and ships a finished, published video.
- LLM-written script and title variants
- Synthesized voiceover across three text-to-speech providers
- AI-generated and stock imagery, selected and composed automatically
- Automated video assembly
- Direct publishing to YouTube, TikTok and Instagram
It is built as a resumable background pipeline. Every step is checkpointed and logged, so a failure at step six resumes at step six instead of restarting from step one. Voice and video vendors sit behind provider abstractions and can be swapped without touching the pipeline. It is multi-tenant from the ground up.
Technologies: OpenAI, DALL·E, ElevenLabs, Google TTS, OpenAI TTS, Pexels, FFmpeg, and OAuth publishing to YouTube, TikTok and Instagram.
Decision engines we have shipped
These are live in production systems, not demos:
- Pricing engines that account for distance, vehicle class, staffing requirements and repositioning cost
- Schedule feasibility analysis — answering whether a multi-stop itinerary can actually be executed, before anyone commits to it
- Intelligent assignment — matching jobs to people by availability, certification, location and constraint
- Document and photo extraction — turning captured paperwork and field images into structured records
- Insight engines combining deterministic rules with LLM interpretation, so the output is explainable rather than a black box
AI inside the product, scoped to your data
In-product generation and assistance, always bounded by the tenant’s own data:
- Generated training programs and multi-week plans
- Generated itineraries and schedules
- Assistants that answer from the client’s records, not the open internet
- Automated analysis and narrative reporting over operational data
Cost control and correctness
Two things separate AI that survives contact with a real business from AI that gets switched off after the first invoice.
Metered billing. We build per-tenant AI credits, plan allowances and usage tracking into the product. AI spend that cannot be predicted or attributed is a liability, not a feature.
Regression testing. AI output drifts. We ship automated benchmark harnesses that re-test analytics and AI output against known-good results, so a model or prompt change cannot quietly degrade the product.
Async by design. AI work runs on background and queue workers and is polled by the interface. Nothing blocks a user request waiting on a model.
Have a process that should not still be manual?
Tell us where the time goes. We will tell you honestly whether AI is the right tool for it.