Build an AI-capable workforce.

Lab57 gives manufacturing teams the practical knowledge, hands-on experience, and confidence to use AI responsibly in the work they already do.

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Technical illustration of an industrial robotic arm above a precision assembly line

HUMAN CAPABILITY × MACHINE INTELLIGENCE

LeadersStrategy + governance

EngineersApplied AI workflows

OperationsUse-case discovery

TeamsEveryday AI fluency

01 / TRAINING

AI fluency that reaches the whole operation.

Role-specific learning for industrial teams—grounded in the decisions, documents, data, and workflows people encounter every day.

01.1

Executive AI literacy

Give leaders a clear view of AI capabilities, limitations, risk, governance, and where investment can create meaningful operational value.

01.2

Role-based workshops

Train engineering, quality, operations, and support teams through hands-on exercises shaped around their real responsibilities.

01.3

Applied generative AI

Teach teams to work effectively with modern AI tools for research, analysis, documentation, troubleshooting, and knowledge access.

01.4

Adoption programs

Turn one-time training into lasting capability with champions, shared standards, use-case coaching, and a practical path to scale.

01.5

Personal AI Agent training

Hands-on training for organizations rolling out personal AI agents to their teams, and for individual teams getting started with one. Learn to delegate real day-to-day work to an agent, review what it produces, and build safe, repeatable workflows around it — from research and drafting to follow-ups, scheduling, and knowledge tasks.

AGENTS COVERED — Muse · Hark · Grok Bot · Dots, plus the habits that transfer between them: clear task briefs, the right context and permissions, human review before anything ships, and responsible use.

02 / APPROACH

Learn it. Apply it. Make it part of the work.

Training is most valuable when people can connect a new capability to a real task, test it safely, and keep improving after the session ends.

A / DISCOVER

Start with the work

Identify where teams spend time, make decisions, and handle knowledge so the learning is immediately relevant.

B / PRACTICE

Learn by doing

Use guided, industry-grounded exercises to build sound judgment—not just familiarity with a tool.

C / EMBED

Create repeatable habits

Translate lessons into shared playbooks, responsible-use standards, and team-led momentum.

The future of manufacturing depends on more than smarter machines. It depends on AI-ready people.

Relevant to the role.
People learn faster when the examples match their work.

Practice over presentation.
Every session should create skills teams can use the next day.

Confidence with judgment.
Effective adoption includes knowing when—and when not—to use AI.

Make your team AI-ready.

Bring practical AI training to your leaders, engineers, operations teams, or wider workforce—built around the work they need to do, including Personal AI Agent training for organizations and individual teams.

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Daniel Gutierrez, founder of Lab57 — Daniel Gutierrez · Founder

ABOUT / DANIEL GUTIERREZ

Industrial experience, translated into practical AI learning.

Daniel is the founder of Lab57 and an AI product leader whose career spans manufacturing engineering, industrial data systems, applied machine learning, and generative AI.

He has led AI and data products from customer discovery through deployment, built solutions for semiconductor and electronics manufacturing, and helped translate complex technical capabilities into practical tools people can trust. That combination of engineering depth and product leadership shapes Lab57’s training: technically rigorous, operationally grounded, and designed for action.

M.S. Industrial & Systems EngineeringSan Jose State University

Co-Founder, Core ImpactCTO + Head of Product

Certified AI EngineerAI Makerspace

Six Sigma Green BeltManufacturing excellence

View LinkedIn ↗

CURRENT / CORE IMPACT

Building intelligent products from factory floor to athlete experience.

At Core Impact, Daniel serves as Co-Founder, CTO & Head of Product, leading an athlete performance platform that brings together wearable hardware, sensor and garment manufacturing, biosensor analytics, a native iOS experience, and AI coaching.

01 / BIOMETRIC INTELLIGENCE

Turning signals into guidance

Daniel built the scoring framework that translates EMG and IMU data into movement quality, power, consistency, and an athlete-facing performance score.

02 / MANUFACTURING + HARDWARE

Bringing the device to market

Drawing on deep manufacturing operations and process development experience, Daniel oversees domestic and overseas sensor and garment production, partners with hardware and firmware engineers on PCB design, fabrication, and assembly, and sources critical device components.

03 / AI COACHING

Making data actionable

He shipped an LLM-based coaching assistant with a structured context model and safety guardrails, giving athletes a clearer way to understand performance data.

SYSTEMS / MANUFACTURING

Thirteen years on the factory floor. One systems view.

Daniel’s manufacturing career progressed from hands-on PCB production to process engineering leadership and industrial AI—using data, controls, and disciplined experimentation to improve how complex work gets done.

13+Years across production and process engineering

20+PCB production processes worked firsthand

8Person pilot-line inspection, packaging + shipping team led

4Domains: PCBs, medical devices, advanced materials + semiconductor AI

AITOMATIC

Industrial AI grounded in expert knowledge

Sr. AI Engineer & Product Manager

Curated and evaluated data for SemiKong, an open-source semiconductor language model; improved aiKO agents used by a chip designer for customer-support ticket responses and by field engineers for electrical-schematic failure diagnosis; and captured subject-matter expertise as facts, rules, and heuristics.

INTRARATIO

From factory visits to production machine learning

Data Scientist → AI & Data Product Manager

Visited semiconductor fabs, PCBA factories, and photonics manufacturing sites to learn each process firsthand, map operational constraints, and identify where machine-learning models could create value. Owned the full product lifecycle for AiCard, IntraRatio’s flagship AI platform, from concept through customer deployment; implemented machine-learning models—including an Isolation Forest outlier-detection application for factory data—from prototype to production; built a RAG LLM application that answered technical questions from uploaded knowledge-base documentation.

TACTUS

Connected process, quality, and production systems

Process Engineer → Process Engineering Manager

Owned lamination and final inspection processes, administered and mapped the company MES, automated pilot-line data collection with Raspberry Pi and Siemens PLC systems, built SPC workflows, ran DOE and validation programs, and led teams bringing TrueWrite Film to shipment.

BOSTON SCIENTIFIC

Statistical control in regulated manufacturing

Manufacturing Engineer II

Led a team of three engineers and one technician supporting a coronary imaging catheter line, combining equipment and process validation with DOE, ANOVA, t-tests, control charts, and weekly SAP Business Warehouse scrap analysis.

GORILLA CIRCUITS

From line operations to predictive process engineering

Operator → Jr. Process Engineer → Process Engineer

Learned more than 20 PCB processes from design through shipment, then built impedance prediction models, improved engineering data collection with InPlan, partnered on CAM automation, created DFM standards, and analyzed process performance with Minitab, JMP, Excel, and Python.

EXPERIENCE / PRACTICE

Training informed by the systems people actually use.

Daniel’s work connects the factory floor, the data stack, and the AI product layer—so Lab57 can teach both the potential and the practical limits of the technology.

01 / MANUFACTURING

Engineering foundations

Experience across process engineering, new product introduction, MES implementation, quality systems, electronics, and advanced manufacturing.

02 / INDUSTRIAL AI

Applied systems

Built and shipped industrial AI products spanning anomaly detection, predictive maintenance, RAG knowledge tools, analytics, and MLOps.

03 / PRODUCT

From idea to adoption

Led AI product strategy, customer discovery, technical prototyping, cross-functional delivery, and the translation of complex systems into useful experiences.

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