Founder-Led AI Studio

Work directly with the engineer leading the project.

AI Workflow Studio is led by Daniel Hallman, an Applied AI Engineer with more than 15 years in mobile development and software consulting. Daniel leads the first call, planning, building, and handoff.

Chattanooga, TN · meetings by appointment

From mobile reliability to applied AI systems.

Daniel began building native iPhone software in 2009 and grew into technical leadership across consumer products, enterprise systems, and consulting. Earlier work includes leading native iOS development at OpenSea, modernizing Trello at Atlassian, and guiding a 15-person mobile, web, and server team.

That background shapes the Studio’s work now: start with the real operating problem, separate repeatable steps from judgment, keep people in control of high-impact choices, and define how the system will be tested and owned.

Daniel leads every engagement. Focused design, data, security, or domain specialists join when the scope needs them, while the client keeps one shared plan and one technical lead.

Experience is labeled honestly.

AI Workflow Studio is newly launched. These examples come from Daniel’s prior engineering roles, not from paid Studio clients. Private measurements are not presented as public proof, and the examples do not promise a result in a future engagement.

Reliabilityproduction stability and incident workPrior engineering role
Deliverybuild and release-system improvementsPrior engineering role
Product flowsimpler account and verification stepsPrior engineering role
Performanceshared sync and startup improvementsPrior engineering role

Clear choices from the first call through handoff.

01

Start with the real work

See how the work moves, where it waits, what goes wrong, and who owns it before choosing a tool.

02

Use AI where it helps

Keep simple rules predictable and use AI only for work that needs interpretation.

03

Keep people in control

Require review and approval when a decision affects money, access, customers, or policy.

04

Plan for daily use

Set the tests, logs, alerts, retries, limits, ownership, and handoff before launch.

05

Show the math and unknowns

Put starting measures, ranges, costs, assumptions, unknowns, and confidence beside every estimate.

06

Recommend the smallest useful next step

End with DIY, Measure First, Optimize, Automate, or Stop. No follow-on project is required.

Start with the Audit, then decide what comes next.

Begin with one fixed-price review. Use the report with your own team, make one process simpler with Optimize, or build a clearly defined system with Automate.

  1. 01
    Audit · $999 fixed

    One operating area, with the ten-page report delivered within five business days of complete inputs.

  2. 02
    Optimize · from $3,500

    Simplify the process when the Audit shows the work itself needs to change.

  3. 03
    Automate · from $7,500

    Scope a tailored build when the Audit shows custom software is worth considering.

AI Workflow Studio

Bring the Problem Your Team Keeps Working Around.

Daniel will show what is causing it, compare the options, and leave you with a clear next step.