AI Automation
Good fit for
- Businesses handling high volumes of repetitive email, documents or intake
- Support and service teams that miss enquiries outside working hours
- Companies that ran an AI pilot and need it made production-ready
Most AI projects stall between a promising prototype and something a business can rely on. The gap is engineering: evaluation, guardrails, data access, error handling, and integration with the systems where the work actually lives.
We build AI into existing operations — document and data processing, customer communication, internal knowledge retrieval, lead qualification and routing — with the monitoring and fallbacks that let you trust the output.
- Remove repetitive work from expensive human hours without losing oversight.
- Respond to customers faster and more consistently, including outside business hours.
- Make internal knowledge searchable and useful instead of buried in files and threads.
- Start with one high-volume process, measure it, then expand where it pays off.
Example deliverables
- Automation opportunity assessment with expected effort and impact
- AI workflow or agent built against your real data and tools
- Retrieval pipeline over your documents and internal knowledge
- Integrations with CRM, helpdesk, email, calendar and internal APIs
- Prompt and output evaluation harness with regression checks
- Human review steps, logging, cost controls and monitoring
Technologies
- Python
- TypeScript
- LLM APIs
- Vector databases
- Retrieval-augmented generation
- Workflow orchestration
- Webhooks & event queues
Projects involving this work
- E-commerce / AI
Yoon Lab
369 Korean skincare products across 30+ brands, sold online and in physical stores across Mexico — filtered by skin concern, with a shoppable video feed and AI skin analysis.
Case study - AI / AgTech
SYBAL
Turning agricultural AI models into production APIs — the engineering layer between a research notebook and a product customers use.
Case study - AI / Voice
AI Receptionist
An AI voice agent that answers the phone and books appointments, built on the Claude SDK.
Case study
- Custom Software DevelopmentBusiness platforms, internal tools and dashboards built around how your company actually operates.
- Backend & API EngineeringAPIs, data models, authentication and integrations designed to stay correct under load.
- Technical ConsultingArchitecture reviews, technology decisions and engineering guidance — with a written recommendation.
Which process would you automate first?
Send us the workflow. We'll tell you honestly whether AI is the right tool for it — and what it would take to ship.
Within 1–2 business days · Working with clients in the United States and internationally