What to Select: "Which NVIDIA Technologies are Currently Used?"

Definitely Select:

• CUDA - Docling's underlying models (PyTorch-based) run on CUDA. This is the foundational technology you're using.
• NVIDIA GPU / GPU Acceleration (may be listed as "NVIDIA GPUs" or "Accelerated Computing") - you're using an NVIDIA GPU to accelerate model inference.
• TensorRT - if Docling or any of your models are optimized/exported with TensorRT (common for inference pipelines). Select if applicable.
• NVIDIA AI Enterprise / NVIDIA NIM - if the form lists these, and you're using any NVIDIA-packaged models or containers.

Likely Applicable (select if listed):

• RAPIDS / cuDF - only if you do GPU-accelerated data processing beyond just inference.
• NVIDIA Triton Inference Server - if you serve your Docling models via Triton.
• NVIDIA DGX / A100 / H100 - if your GPU is one of these, mention the specific hardware tier.

Probably Not Applicable:

• DRIVE (automotive), Jetson (edge/robotics), Omniverse (3D/simulation), Clara (medical imaging) - skip these unless relevant to other parts of your product.

Suggested Short Description for the Form

"We use NVIDIA GPU acceleration (CUDA) to run Docling-based document AI models for PDF parsing, including layout detection, table extraction, and OCR. Our inference pipeline leverages NVIDIA GPUs to accelerate deep learning model execution for enterprise document processing."

Field-by-Field Guidance

• Select "No board seat" or "Observer seat" - at pre-seed, most investors don't take board seats. "Undecided" is fine to leave if you genuinely haven't decided, but investors prefer clarity.

• If you don't have a term sheet yet: select "No"
• If you have one in progress: select "Yes"
• Most pre-seed raises won't have one yet, so likely "No"

• Select whatever your current ARR is honestly. If you're pre-revenue: "$0" or "Pre-revenue"

• If pre-revenue or very early: select "N/A" or the lowest/earliest option available

• "No" if you don't have one yet (common at pre-seed)
• "Yes" if someone has committed

• Set a realistic target, e.g. 3-6 months out from today: something like 09/30/2026 or 11/30/2026

"Why are you raising capital?" (1,000 chars max)

"We are raising pre-seed capital to accelerate product development and early customer acquisition for our AI-powered document intelligence platform. Our system uses NVIDIA GPU-accelerated deep learning models to parse, extract, and structure data from complex PDFs at scale - enabling enterprises to automate document workflows. Funds will be used for engineering hiring (2 engineers), cloud infrastructure, and landing our first 10 paying customers. We are targeting enterprises in legal, finance, and compliance verticals where unstructured document processing is a core bottleneck."

"We use NVIDIA GPU instances (p3/p4/g5) on AWS with CUDA to run Docling-based document AI models for PDF parsing, layout detection, and table extraction. Planning to adopt TensorRT for optimized inference as we scale."

Why this works:

• p3/p4/g5 instances = AWS instance families powered by NVIDIA V100, A100, and A10G GPUs - directly maps to "NVIDIA technology on AWS"
• CUDA = the core technology running under your models
• Docling = shows real, specific usage (not vague)
• TensorRT = shows forward-looking adoption, which investors and NVIDIA both like to see

"Using NVIDIA GPU instances (g5/p4) on AWS with CUDA for GPU-accelerated PDF parsing via Docling AI models. Planning TensorRT adoption for faster inference at scale."