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Tribucorp
Service · Enterprise AI development

AI that solves real problems Not pretty demos.

We build production AI systems on Dell + NVIDIA: multi-agent systems, enterprise RAG, computer vision, digital twins and predictive ML. From a POC in 3 weeks to 24/7 operation.

3 wks
Working POC
23
Products in production
2
NVIDIA + Dell partners
Summary

Tribucorp builds custom production AI systems: LLMs with RAG, anti-hallucination multi-agent systems, computer vision on NVIDIA Metropolis, digital twins and predictive ML. We work with clients in healthcare, water, construction, agtech and media from Chile across LATAM. We deliver a POC in 2–4 weeks and operate Dell + NVIDIA infrastructure on-prem or hybrid with enterprise SLAs.

Technical capabilities

The full modern AI stack, operated in production.

We choose the technique based on the problem, not the other way around. Every vertical in the group combines several capabilities — these are the ones you'll find working with us.

LLMs & Generative AI

Fine-tuned language models, enterprise RAG and multi-agent systems with proprietary context.

LLaMA Claude GPT-4 NeMo LangGraph

Computer Vision

Medical segmentation, agricultural detection, real-time video analysis with NVIDIA Metropolis.

TAO Toolkit DeepStream YOLO SAM Metropolis

Digital Twins

Digital twins of operations to simulate, predict and optimize — Agua.AI saves up to 42% of non-revenue water.

Omniverse Isaac Sim Modelica FMU

Multi-Agent Systems

Agent systems that cross-check each other (anti-hallucination) for critical domains like healthcare and compliance.

CrewAI AutoGen LangGraph Semantic Kernel

Voice & Audio AI

STT, TTS, voice cloning and AI-driven music generation.

Whisper Coqui ElevenLabs Riva Bark

Predictive ML

Predictive models for crop yield estimation, anomaly detection and financial scoring.

XGBoost Prophet PyTorch TensorFlow Triton
How we work

From the first conversation to AI running 24/7.

01

Discovery

We understand your domain, data and constraints. We define success in business metrics, not model metrics.

02

Rapid prototype

We build a working POC in 2–4 weeks with real data — no demos with synthetic data.

03

User validation

The team that will use the AI validates it before moving to production. We iterate until it is genuinely useful.

04

Productionization

Scalable architecture on Dell + NVIDIA, MLOps, observability, SLAs and internal team training.

05

Continuous operation

Drift monitoring, scheduled retraining and model evolution alongside the business.

Frequently asked questions

What people ask before signing.

How long until I have a working POC?
Between 2 and 4 weeks. We work with your company’s real data from day one and deliver a prototype that already produces value — not a demo with synthetic data.
Do you work with on-premise or cloud data?
Both. As Dell Partner Services we deploy on-prem infrastructure when data cannot leave the premises (healthcare, banking, government) and use NVIDIA AI Enterprise for hybrid environments.
Which AI models do you use — OpenAI, Claude, proprietary models?
Whichever fits the case. We use OpenAI, Anthropic Claude, fine-tuned LLaMA, NVIDIA NeMo or proprietary models. We always evaluate by total cost, data privacy and quality in the specific domain.
Do you offer an accuracy guarantee?
We sign SLAs on agreed business metrics (e.g. ≥94% precision in pest detection, ≥99% recall in clinical anomalies). We use anti-hallucination multi-agent architectures for critical domains.
Do you train our internal team?
Yes. Training is included in every project — we don’t want you to depend on us forever. We transfer knowledge, documentation and runbooks.
How much does an AI project cost?
It depends on scope. A POC starts at USD 15K–30K. A production system with infrastructure typically runs between USD 80K and 350K depending on the case. Free quote after the discovery session.

Got a concrete problem that AI can solve?

30 minutes of conversation is enough to know if it makes sense. We bring a technical team — not salespeople.