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AI Consulting & Data Architecture

Frontier AI solutions for enterprise

As a machine learning engineer, I’ve spent my career building data infrastructure and ML/AI systems for Fortune 100 teams. I work closely with you to understand how your business operates, strengthen its data foundation, and build agents and automations around it.

Discuss a projectSee how it works

Tech Stack

  • Google Cloud Platform
  • AWS
  • Databricks
  • Snowflake

How we work

  1. Step 01

    Discovery

    The initial call is an open ended working session. Some clients arrive with a specific idea, such as a data agent, while others want to explore what their business could build within a given budget. The goal is to leave with a clear direction for what we’ll create together. I’ll also assess your current data environment to understand what’s available, what needs work, and where we should begin.

  2. Step 02

    Development

    Building is done in your environment. I prefer to use an agile methodology on focused sprints, with frequent communication to keep priorities, progress, and expectations clear. Enterprise quality + results is the focus, which include security, reliability, and a foundation for scale.

  3. Step 03

    Deploy to Prod

    Our goal is to deliver a production-ready agent, system, or automation that your company will own. That includes secure CI/CD, compliance controls, SAST/DAST, and monitoring. Before launch, we validate it across lower lifecycles and, for agents, run evaluations that catch regressions.

Monitoring

Live dashboards and automation are built out for reporting after deployment. We track usage, incidents, costs, throughput, and latency percentiles. For agents, things like tool failures, token usage, model data are all monitored.

Hourly answer latency46.43s

Use the arrow keys to move through the data, Home and End to jump to the ends, Escape to clear.

Line chart of latency_seconds_50th and latency_seconds_90th, May 14 to Jun 12.
Categorylatency_seconds_50thlatency_seconds_90th
May 1427s (27s–63s)63s
May 1529s (29s–70s)70s
May 1626s (26s–64s)64s
May 1734s (34s–75s)75s
May 1891s (91s–242s)242s
May 1932s (32s–72s)72s
May 2037s (37s–82s)82s
May 2131s (31s–69s)69s
May 2242s (42s–90s)90s
May 2336s (36s–73s)73s
May 2439s (39s–81s)81s
May 2533s (33s–65s)65s
May 2645s (45s–94s)94s
May 2735s (35s–77s)77s
May 2841s (41s–88s)88s
May 2929s (29s–63s)63s
May 3043s (43s–96s)96s
May 3139s (39s–80s)80s
Jun 131s (31s–68s)68s
Jun 25s (5s–8s)8s
Jun 38s (8s–10s)10s
Jun 433s (33s–72s)72s
Jun 540s (40s–88s)88s
Jun 646s (46s–104s)104s
Jun 729s (29s–76s)76s
Jun 835s (35s–83s)83s
Jun 939s (39s–225s)225s
Jun 1027s (27s–91s)91s
Jun 1142s (42s–278s)278s
Jun 1246.43s (46.43s–75.73s)75.73s

What Next?

Additional sprints are always available after handoff if you need to connect another data source or improve an existing application. We can make a custom plan depending on your needs whether it will just be a weekly call or feature development.