Austin, TX

AI Consulting in Austin

I help mid-market companies, enterprises, and nonprofits in Austin design and deploy practical AI systems—especially AI agents, RAG (retrieval) pipelines, and evaluation/safety guardrails—so prototypes turn into reliable workflows.

Austin-based. Available for Austin/Central Texas engagements and remote work across the U.S.

Book a 15-Minute Intro Call Email Me

What I Help Austin Teams Build

1. AI Agents and Workflow Automation

Systems that use LLMs to take actions through tools (APIs, internal services, databases), with clear boundaries and failure handling.

Examples of work you might bring me:

  • Designing an agent workflow for internal operations (triage, summarization, routing, drafting)
  • Adding tool-use safely (permissions, logging, guardrails)
  • Defining what the agent should not do and how it escalates to a human

2. RAG Systems for Internal Knowledge

Retrieval-Augmented Generation for your documents, policies, and knowledge base—built with attention to data handling, chunking, retrieval quality, and evaluation.

Examples:

  • Architecture for ingesting PDFs/docs into a searchable system
  • Improving answer quality using better retrieval and evaluation loops
  • Designing "grounded answers" behavior and citation-based responses

3. LLM Evaluation and Safety Guardrails

A practical evaluation approach so you can measure risk and quality before production.

Examples:

  • Building an evaluation harness for outputs (quality, safety, policy checks)
  • Creating test sets from real workflow scenarios
  • Defining success metrics and monitoring signals

4. Team Training That Matches Real Workflows

Hands-on training for leaders and teams to adopt AI responsibly and consistently.

Examples:

  • Executive AI literacy for decision-making
  • Team workshops: prompting, verification habits, safe usage patterns
  • Customized examples tied to your internal workflows (under NDA if needed)

Who I Work With in Austin

I'm a strong fit if you're an Austin-area organization that:

Has real workflows (not just demos) and wants practical AI adoption
Needs engineering-quality delivery (architecture + implementation)
Cares about reliability, safety, and measurable outcomes

Common profiles:

  • Mid-market teams looking to operationalize AI quickly and safely
  • Enterprise teams deploying GenAI where quality and risk matter
  • Nonprofits who need trustworthy systems and clear boundaries with limited resources

How an Engagement Typically Works

I keep the process simple and execution-oriented.

1

Intro + Scope (15–30 minutes)

We align on your goal and constraints (data, risk, timeline, stakeholders), what "success" means in measurable terms, and whether this is a build, advisory engagement, or training.

2

Discovery and Workflow Mapping

I map the actual workflow, inputs/outputs, and failure modes. For AI systems, this step matters more than the model choice.

3

Architecture + Evaluation Plan

You get a clear plan: system design (components, data flow, boundaries), evaluation approach (what we will measure and how), and safety/guardrails considerations appropriate to your use case.

4

Build and Iterate

Hands-on implementation support where it makes sense, plus iteration based on evaluation results and user feedback.

5

Handoff and Enablement

Documentation + team enablement so the system can be maintained and improved.

What I Optimize For

I optimize for:

  • • Practical delivery, not "AI theater"
  • • Workflows that people actually use
  • • Measurement and evaluation (so you can trust what ships)
  • • Clear boundaries, escalation paths, and safe defaults

I don't optimize for:

  • • Flashy demos with no path to production
  • • Over-complicated architectures that can't be maintained
  • • Claims that can't be validated by data or evaluation

Experience and Background

  • Senior AI Engineer (contract) building LLM safety guardrails, RAG ingestion, and evaluation pipelines for a learning platform
  • Prior work in time series forecasting and applied ML in an enterprise setting
  • CEO/leadership role in an Austin-based AI nonprofit focused on practical AI education and community programming

If you need references or examples, we can discuss what can be shared appropriately (some work is covered by confidentiality).

Frequently Asked

Do you only work with Austin companies?

No. I'm Austin-based and can do local engagements in Central Texas, but I also work remotely with teams across the U.S.

Can you come on-site in Austin?

Yes, depending on scheduling and scope. For training workshops or stakeholder alignment, on-site can be useful.

Do you sign NDAs?

Yes, for consulting builds and internal workflow work, NDAs are common.

What's a typical engagement size?

It depends on scope. Some engagements are focused advisory or architecture reviews; others include hands-on implementation and team training.

Do you provide training only (no build)?

Yes. Training engagements can stand alone, especially for organizations that want safe adoption and consistent team practices.

Ready to Talk?

If you're in Austin and exploring AI agents, RAG systems, or evaluation/safety guardrails, I'm happy to do a quick intro call to see if there's a fit.

Book a 15-Minute Intro Call Email Me