AI that
generates ROI
DashOne embeds Forward Deployed Engineers with your team for 4–12 weeks and turns your AI roadmap into production systems. Not slides. Not pilots. Production.
DashOne embeds Forward Deployed Engineers with your team for 4–12 weeks and turns your AI roadmap into production systems. Not slides. Not pilots. Production.
01 · Definition
A senior engineer who deploys with your team — not for it. Origin: Palantir. Now standard at Anthropic, OpenAI, and every serious AI infra company. The role exists because shipping AI isn't a research problem — it's an integration problem.
Our engineers write production code in your repo. Review PRs. Own the deploy. The output is software that runs, not a deck that recommends.
Measured by what shipped and what moved — conversion, latency, accuracy. Not by hours billed or workshops run.
We join your Slack. Sit in your standups. Pair with your team. The handover is your team running the system — on their own.
02 · The difference
Both important. Different jobs. Most companies hire one and need the other.
The 95% problem
MIT reports 95% of enterprise AI pilots fail to reach production. The cause isn't the model — it's the missing engineering layer between the model and the business. That layer is what DashOne's FDEs own.
03 · Engagements
01
Multi-step agents with proper orchestration, tool use, MCP integrations, observability and cost guardrails. Not demos — systems your users can rely on.
02
Memory, retrieval, prompt caching, and the architecture that makes responses accurate, cheap and reproducible. The work that separates shipping from prototyping.
03
Policy engines outside the model, output validation, red-teaming, structured evals tied to your business metrics. The compliance and reliability layer.
04
Your team owns it after we leave. Pairing, code reviews, internal docs, runbooks. The deliverable is your engineers doing this without DashOne.
04 · How it works
Four phases, fixed scope, no surprises. Every engagement follows the same structure so your team knows what to expect — and when.
We map your systems, data flows, and team capabilities. We identify the AI use case with the highest ROI and lowest integration risk. Output: a scope doc both sides sign off on.
We design the system: model selection, context engineering, tool integrations, guardrails, observability. No code yet — but every decision is documented and reviewable.
FDEs work inside your repo, your CI/CD, your stack. We ship in weekly increments. Your team reviews every PR. No black boxes.
We hand over runbooks, evals, and monitoring dashboards. Then we pair with your team until they own it. We don't leave until the system runs without us.
Work modalities
Every engagement starts with Discovery — included in the hours. Then you choose how deep you want to go.
A senior FDE integrates with your team on a weekly hour commitment. Right for ongoing engineering muscle embedded in your operation.
Autonomous AI agents built, trained and deployed to replace specific repetitive workflows. After training, they operate independently — no ongoing cost.
A specific deliverable, quoted by scope. A dedicated DashOne expert handles it start to finish — from architecture to handover.
05 · Results
07 · Stack
You don't have to change everything or learn one more tool. We integrate into what you already use — and help you reduce the number of licenses you're paying for.
08 · The team
Senior engineers with 20+ years shipping compliant, production-ready software — most recently as FDEs for companies integrating AI into their core product. We work with a small number of teams at a time so every engagement stays high-leverage.
"The gap between 'generally intelligent' and 'specifically useful' is where most AI work fails. Closing that gap is the entire job."
09 · Clients
“We went from a stuck AI pilot to a working agent in production in 6 weeks. DashOne's engineers joined our standups, reviewed our PRs, and left us owning the system — not dependent on them.”
“We had the model. We had the data. What we were missing was the engineering layer that connects them to our product. That's exactly what DashOne built — and documented — before they left.”
“Most AI consultants deliver a report. DashOne delivered a working system with evals, monitoring, and a team that knows how to maintain it. That's the real deliverable.”
10 · FAQ
Engagements run 4–12 weeks depending on scope. A focused sprint (one agent or integration) is typically 4–6 weeks. A full platform build is 8–12. We define scope before we start — no open-ended retainers.
No. We work alongside whatever team you have — from a solo CTO to a 20-person engineering org. The handover is designed so your existing engineers own the system after we leave, without needing specialized ML expertise.
Staffing fills a seat. DashOne owns an outcome. We scope a specific deliverable, build it, and leave your team capable of running it. We're not billing hours — we're shipping a working system.
We're model-agnostic but opinionated. For most enterprise use cases we recommend Claude (Anthropic) for reasoning and safety, OpenAI for breadth of integrations, and open-source models (Llama, Mistral) when data privacy or on-premise deployment is required.
You own everything — code, docs, evals, runbooks. We offer optional post-engagement support for critical incidents, but the goal is that you don't need us. If you do, we're reachable. Most clients run independently within 30 days of handover.
Talk to Dante below or take the AI Readiness assessment. Both routes end at a 30-minute discovery call with the DashOne team — no sales pitch, just a clear picture of whether and how we can help.
11 · Start a project
Chat with Dante and get all your questions answered.
