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Tech partners for strategic AI implementation

Architecting Agentic Workforces
& custom AI solutions
for heavy industry.

TECH PARTNERS

Architecting
agentic workforces
& custom AI solutions
for heavy industry.

We help enterprises with complex business processes

critical workflows through the strategic deployment of

Patagonian is your tech consulting partner. We help enterprises with complex business processes Architect, Re-Engineer and Automate critical workflows through the strategic deployment of agentic workforces, custom software, AI tools and nearshore teams.
Innovation in action

Solving the problems
that cost you most

From energy plants to pharma labs — here's where AI and custom software deliver measurable outcomes on the workflows that matter most.

<5% of operating time consumed by shift handovers
20% reduction in network costs by rewiring supply chains with AI
60% faster documentation production with AI, fewer errors, less workload

Are manual shift handovers
causing plant incidents?

AI-powered shift handover dashboard
40% of plant incidents start at the handover
AI Shift Intelligence

Agentic workflows that structure, validate, and transfer critical operational data automatically — so nothing falls through between shifts.

Explore our approach

Is unplanned downtime
draining your margin?

Predictive maintenance monitoring dashboard
30% avg. reduction in unplanned stoppages
Predictive Maintenance

Real-time sensor integration and ML anomaly detection that flags failures before they happen — dispatching automated alerts to the right teams.

See how it works

Are data entry errors slowing
pharma compliance?

OCR pharmacovigilance pipeline
85% reduction in data entry errors
OCR + ML Pipeline

Serverless AWS platform using OCR and automated ML pipelines to extract, validate, and summarize adverse event data from PDFs and XML files.

Read the case study

Want to see how we've applied this across Oil and Gas, Manufacturing, and Logistics?

Explore all insights
Our 3W Approach

Orchestration of services

Engagements may start in one W, but meaningful outcomes
are achieved when all three work together.

Workforce

We multiply operational throughput without linear hiring by augmenting teams with AI training, agentic workforces, and specialized talent — elastic human-agent teams that scale to meet demand.

Workbench

We embed AI as a Decision Intelligence engine: secure governed cloud infrastructure, data lakes, dashboards, agent platforms, and seamless integrations across legacy systems.

Workflows

We redesign critical processes using AI-augmented and agentic flows, transforming human-dependent bottlenecks into dynamic automated operations that actually create leverage.

Client Stories

What our clients say

What our clients say
"Working with Patagonian has been a game-changer for our recruiting process. Their timely support and genuine advocacy have not only streamlined our hiring but also ensured we find the right talent for our team. They are incredibly flexible with our ad-hoc and ever changing needs. We couldn't ask for a better partner in our recruitment journey."
Ilse Calderon Chief of Staff
What our clients say
"Patagonian cares about people and delivery. The fact that they've been with us from the start and were patient, supportive, committed, and flexible is excellent. We are extremely satisfied."
Steven Krubiner Founder & CEO
What our clients say
"They are the most timely, efficient, and effective team I have ever worked with! I can always trust them to get whatever is needed done!"
Katie Jones
What our clients say
"Atmos Fragrance had the pleasure of partnering with Patagonian on a mission-critical quality assurance project. Their technical and testing abilities were truly impressive. Patagonian didn’t just deliver a service, they became a trusted partner. I wholeheartedly recommend them to any organization seeking top-tier software expertise"
Q. Wade Billings Chief Information Technology Officer

Latest blog posts

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Connected field worker: gestión de equipos de campo con IA agéntica en oil & gas IA y Oil & Gas
Agente IA Monitoreo activo
October 1, 2026  ·  7 min read

IA agéntica en oil & gas: cómo gestionar equipos de campo

Key takeaways
  • En muchas operaciones de oil & gas, la coordinación de campo todavía depende de radio, WhatsApp y handoffs verbales. Quienes supervisan no tienen visibilidad en tiempo real y las cuadrillas entrantes reciben información parcial en cada cambio de turno
  • El 89% de las organizaciones ya usa IA de forma regular, pero solo el 37% le atribuye algún impacto positivo en el EBIT. Las que logran un impacto significativo suelen haber rediseñado sus workflows, no solo sumado IA
  • Connected Field Worker, de Patagonian, guía cada tarea desde el celular (permiso de trabajo, JSA, mantenimiento) y la registra con hora, responsable y ubicación a medida que ocurre. El supervisor ve el estado de cada persona en un tablero en tiempo real
  • En EE.UU., se proyecta que la IA pase de menos del 20% a más del 50% del gasto en IT de las compañías de oil & gas hacia 2029, con cerca de la mitad hoy destinada a optimización de procesos
Read full article
From this article Q&A
IA agéntica en oil & gas: cómo gestionar equipos de campo

Es un proceso operativo, como un permiso de trabajo o un cambio de turno, ejecutado por un agente de IA que guía cada tarea desde el celular. El agente registra los datos a medida que ocurren, así que la cuadrilla entrante y quien supervisa ven permisos abiertos, restricciones de seguridad y el estado de cada tarea en tiempo real.

Principalmente la integración con sistemas legacy, los datos fragmentados y la gobernanza. Según McKinsey, el sector está entre las industrias de entornos fragmentados que avanzan más lento en agentes de IA. Aun así, la inversión crece: según Deloitte, el gasto en IA de las compañías de oil and gas de EE.UU. subió 40% en 2025. En Patagonian creemos que primero se rediseña el proceso y después se suma la capa agéntica.

Definiendo desde el inicio cómo se va a medir y rediseñando el proceso, en lugar de sumar IA sobre el existente. Según McKinsey, solo el 37% de las organizaciones atribuye algún impacto positivo en el EBIT a la IA, y las que logran un impacto significativo tienen el doble de probabilidad de contar con procesos definidos para medirlo.

Empezando por rediseñar el proceso en torno a cómo trabaja realmente la gente en campo (permiso de trabajo, JSA, handover de turno) y, recién después, sumando la capa agéntica. También conviene definir qué tareas puede ejecutar un agente y cuáles requieren validación humana, y cómo se va a medir el impacto. Esa es la secuencia que seguimos en Patagonian.

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