An AI engineer who builds what he recommends
Ariel Salem
Senior Software & AI Product Engineer · Founder, Dot AI Consulting
I'm an AI engineer with more than 10 years of hands-on experience building automations, agent workflows, production integrations, and internal tools. My focus is not AI hype or abstract theory — I help teams understand what AI can realistically do, where it breaks down, and how to turn promising ideas into safe, useful systems that save real time.
I currently work as a software engineer at LaunchDarkly, where I build autonomous agent systems. Before that, I was an AI engineer at Equall.ai, a legal AI platform, where I developed document search pipelines, contract Q&A, and structured data extraction tools.
Before advising, I build. Recommendations come from shipping real automations — not slide decks about what AI might do someday. I work with small and mid-sized teams that want adoption to be practical, measurable, and grounded in how people actually work.
You do not need a machine learning research team to start using AI well. You need clear use cases, well-designed automations, sensible guardrails, and a way to measure whether the work is actually helping.
Why Dot AI Consulting exists
The gap between advice and implementation
Many AI advisors can explain what is possible. Many software developers can build what they are told. Dot AI Consulting is designed to connect the two: identify the workflow that matters, define the right level of AI, implement a focused solution, and leave the client with a system the team can understand and operate.
The firms and teams that benefit most are not looking for a research project or a generic AI assessment. They have a real workflow, a clear cost of doing nothing, and a need for someone who can both evaluate the problem and build the solution. That is the gap Dot AI Consulting is built to fill.
Founding clients
Two founding-client engagements currently available
Dot AI Consulting is accepting a small number of initial engagements at a discounted rate in exchange for a publishable case study. If your team has a real workflow problem and is willing to share results, this is the fastest path to a working system at below-market cost.
Discuss a founding engagementExperience
Where I've shipped AI in production
LaunchDarkly
Software Engineer
Building autonomous agent systems — AI-driven workflows that make decisions, call tools, and operate with minimal human intervention inside a production software platform.
Equall.ai
AI Engineer
Developed AI tooling for a legal AI platform — including document search pipelines, contract Q&A, structured data extraction, and integrations with legal workflows and data sources.
Technical background
10+ years across the full stack
Production experience, not just familiarity — across the areas that matter most for AI adoption and implementation.
Working principles
AI is not always the answer
Some workflows need better process design, cleaner data, or simpler software rather than a custom AI system. Dot AI Consulting evaluates the business problem first and may recommend an existing tool, a conventional automation, or no AI implementation at all.
Additional AI training
Credentials and coursework
Supplementary to 10+ years of production engineering experience.
Google AI Essentials
Anthropic AI Certification
Anthropic
Fit and non-fit
When Dot AI Consulting is not the right partner
Being honest about fit saves time on both sides.