I build and improve AI agents, voice workflows and SaaS products connected to your business systems. Bring a new product, an integration that needs fixing or a manual process to automate. I handle the backend, interfaces, billing and deployment.
Explore the systems, integrations and engineering decisions behind my work — and how that experience can apply to your project.
I built a voice commerce system that connects Retell AI with WooCommerce product data, on-screen product selection and an order workflow. The SaaS backend handles store isolation, usage accounting and billing.
I built a monitoring pipeline that collects website changes, identifies differences and uses structured AI analysis to produce prioritized findings and reports. The product connects the analysis pipeline with dashboards, alerts and billing.
I built a browser-based scanner for public AI chatbot integrations. It combines configuration checks and interaction probes with severity scoring, evidence and remediation-oriented reporting.
I built an AI receptionist product with voice-agent configuration, call handling, appointment intent, transcripts and clinic dashboards. The product includes subscriptions, administration and workflows for staff review.
Models create capability. The surrounding system determines whether that capability becomes dependable software, a usable workflow, and a business result.
Bounded model tasks with explicit inputs, outputs, and review paths.
Durable state and boundaries around probabilistic behaviour.
Interfaces where users can inspect, operate, and correct the system.
The controls that support everyday product operation and maintainability.
Mobile releases, BLE protocols, offline-first products, commerce, and client delivery are supporting evidence: the engineering depth existed before the current AI cycle.
I am most useful where a capable prototype has to become a product that other people can operate and trust. I work across architecture, backend, product UI, integrations, deployment, and the uncomfortable details between them.
My earlier work spans native mobile, BLE hardware, health products, SaaS, and e‑commerce. That range now informs how I build applied AI systems: with explicit boundaries, real operator workflows, and respect for production failure modes.
Make the data, workflows and integration boundaries explicit.
Use conventional software to contain probabilistic behaviour.
Logs, controls, reports, and review flows are part of the product.
Deliver software that can be deployed, maintained and extended.
AI integrations and complete software products, shaped around your business workflow.
Connect AI to the tools, data and business actions your team uses.
Explore services ↗02 / VoiceVoice agents built with Retell AI or Vapi, connected to commerce, reception and business software.
Explore voice AI ↗03 / ProductsBackend, interfaces, subscriptions and deployment around your AI product.
Explore product engineering ↗Technical breakdowns of the systems I build and the decisions that connect AI to business workflows.
How I approached voice commerce in Slivo: product data, Retell AI, visual selection and the SaaS layer around the agent.
Read the article ↗Tell me what you want to achieve, the tools you already use and where the process gets stuck. I can help define the approach, identify the integrations and develop the system.