95% of enterprise AI projects fail to move from pilot to production (MIT). In LATAM, 80% never deliver the value promised (RAND, Gartner 2026). It's not the model. It's the engineering layer missing between the model and your business.
01 · Diagnosis
Recognizing where you're stuck is the first step. DashOne exists to solve exactly this.
Works in demo, not in prod
The model performs great in the sandbox. The moment it touches your real systems, everything breaks. You need the engineering layer between the LLM and your product.
Nobody to hire
The role grew 800% in job postings in 2025. OpenAI, Anthropic, Google, and Palantir pay FDEs $215K–$310K base. The search takes 8–12 weeks. You need this solved now.
Strategy vs. execution
56% of companies in Mexico still can't articulate the commercial value of AI (KPMG 2025). You don't need another deck. You need a first system that moves a number.
Big 4 or in-house
A traditional consultancy hands you slides and leaves. Hiring an AI engineer takes 6–9 months. The embedded FDE is the third option most people don't know exists.
Learn, don't depend
Abstract training doesn't work. Your team learns by building alongside someone who's already done it — in your repo, on your stack, solving your actual problems.
02 · Services
No consulting. No workshops. Code in production with your team.
Multi-step agents with real orchestration, tool use, MCP integrations, observability, and cost guardrails. No demos. Systems your users can actually rely on.
Memory, retrieval, prompt caching, and the architecture that makes responses accurate, cheap, and reproducible. The work that separates a prototype from a product.
Policy engines outside the model, output validation, red-teaming, structured evals tied to your business metrics. The compliance and reliability layer.
Your team owns it after we leave. Pair programming, code reviews, internal runbooks, documentation. The deliverable is your team doing this without DashOne.
03 · Methodology
Four principles that define every engagement. No exceptions.
You know exactly what gets delivered and when. No scope creep, no endless meetings, no invoices that keep climbing.
We write code in your repo. We review PRs. We own the deploy. The output is software that runs, not a deck that recommends.
We're in your Slack. We're in your standups. We pair with your team. Handover means your team running the system, solo.
Conversion, latency, accuracy, real savings. Not billable hours or workshops run.
04 · Comparison
Four paths. Only one delivers a production system with your team operating it.
| Option | Timeline | Outcome | Team ownership |
|---|---|---|---|
| In-house AI Engineer | 6–9 month search | You commit long-term before knowing if your use case works. $215K–$310K base annually. | Yes, eventually |
| Big 4 consultancy | 3–6 month discovery | Decks. Workshops. Recommendations. Your team is just as lost when they leave. | No |
| Turnkey vendor | Fast at the start | Black box. If your use case shifts even slightly, it breaks. Zero ownership on your side. | No |
| DashOne FDE ✦ | 4–12 weeks | Production system. Fixed scope. You walk away with knowledge, not dependency. | Yes, from day one |
The third option
The embedded FDE is the model OpenAI, Anthropic, and Palantir use internally to get their enterprise customers to production. DashOne brings that model to companies in LATAM, with fixed scope and real delivery.
05 · Ideal profile
DashOne isn't for everyone. We work with a small number of teams at a time.
You've already validated the use case. You need the engineering to get it to production. You have the model, the approved budget, and a pilot that won't scale.
You'll hire eventually. In the meantime, you need the system to exist and your team to understand how to run it.
You're not outsourcing your competitive edge. You want your team to understand every architecture decision. The deliverable includes the knowledge.
You have the process documented. You have the data. What's missing is someone to build it at the reliability level a production system demands.
06 · Deliverables
After an engagement with DashOne, here's what you have — and what you don't.
✓ What you have
✗ What you don't have
07 · Resources
Writing from the team on enterprise AI architecture. Opens on any device.
Why system design replaces prompt design. From Karpathy to Gartner.
Open → ArchitectureThe 8 layers from end user to model. The full enterprise stack.
Open → Executive guide · ROI9 chapters. Why 95% of pilots never scale. The numbers, risks, and ROI levers.
Open →08 · Team
DashOne is led by Jules Avila. 20+ years shipping software in production, the last few as an FDE helping companies integrate AI into their core product. Works with a small number of teams at a time to keep every engagement high-leverage.
Based in Mérida, Yucatán. Works globally. Available for 4-to-12-week engagements.
"The gap between 'generally intelligent' and 'specifically useful' is where most AI work fails. Closing that gap is the entire job."
09 · Start a project
Tell us about your team, your stack, and what you're trying to ship. We respond within 48 hours.