Our Team

The people behind every Date Palm Media product — from MyPaintBuckets to RotoEdge Pro. A small team with a long track record of shipping software that runs businesses.

Joseph Dattilo

Founder & CEO · UI Architecture

Joseph founded Date Palm Media after 25+ years of engineering, product leadership, and systems architecture. He built and ships MyPaintBuckets — a production SaaS used by painting businesses to manage crews, jobs, and operations — which has run in production for years and continues to serve real clients today. His current focus is AI-native development and agentic engineering: building systems where AI acts as a real contributor, not just an autocomplete tool. Every engagement starts the same way: Joseph learns how your business actually works before a line of code is written.

DjangoDockerFastAPIKubernetesUI Architecture

Katherine Dattilo

Graphic Design & Brand Identity

Katherine is a fine artist and professional graphic designer who has created the logo and visual identity for Date Palm Media projects including MyPaintBuckets and the current company brand. She contributes to visual styling and design reviews across active projects, bringing an artist's eye to how the work is presented.

Fine ArtLogo DesignDesign ReviewGraphic DesignBrand Identity

Muhammad Hidayatulloh

Senior Engineer

Hidayatulloh has been with Date Palm Media since its founding and has worked on every product the company has shipped. His strengths are Django, React, and Angular — and he has a particular reputation for tracking down and eliminating bugs that other developers can't find. If it was built at Date Palm Media, he has had his hands on it.

ReactDjangoPythonAngularAPI Design

Mark Dearman

Senior Engineer · DevOps

Mark has been engineering at Date Palm Media through Speak Meetings and MyPaintBuckets — two products with very different demands that both required him to own backend systems end to end. He has direct experience with NLP pipelines and agentic AI integrations from the Speak era, and carries that into modern LLM work. He also runs our build and deployment infrastructure: Jenkins, Kubernetes, and CI/CD at every layer. A strong backend developer who ships across the full stack when the job calls for it.

NLPCI/CDReactDevOpsPython
AI Development Tools

The Full Team

The human team works alongside these tools in production — not as a novelty, but as a deliberate part of how we build. Each model is matched to what it actually does well. Every engagement has the infrastructure to keep that work safe and auditable.

Anthropic Claude

Anthropic Claude

Complex Reasoning & Agentic Workflows

Claude excels at long-context reasoning, multi-step task execution, and following nuanced instructions reliably. We use it where the work requires sustained coherence across a complex chain — architecture decisions, agentic development pipelines, and production integrations that need to behave predictably at every step.

  • check_circle Long-context reasoning across large codebases
  • check_circle Multi-step agentic task execution
  • check_circle Reliable instruction-following in production pipelines
  • check_circle Code generation, review, and refactoring at scale
OpenAI

OpenAI

Embeddings, Search & Structured Output

OpenAI's models are a strong fit for embedding-heavy workloads, semantic search, and structured output pipelines. We have production experience with the OpenAI API going back before the current LLM wave — including early NLP systems built when GPT was still a research model.

  • check_circle Embedding generation and semantic search pipelines
  • check_circle Structured output and function calling
  • check_circle GPT-4o and o-series reasoning tasks
  • check_circle Legacy and modern API compatibility
Local & Fine-Tuned Models

Local & Fine-Tuned Models

Privacy-First & Domain-Specific Inference

Open-weight models deployed on local infrastructure are the right call for privacy-sensitive workloads, domain-specific tasks, or cost-controlled inference at scale. We deploy, serve, and fine-tune these models — your data stays on your infrastructure.

  • check_circle Local model deployment and inference serving
  • check_circle Domain-specific fine-tuning on proprietary data
  • check_circle Privacy-first workloads with no third-party data transfer
  • check_circle Cost-controlled inference at volume

Ready to start a project?

Tell us what you're trying to build. We'll tell you how we'd approach it.

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