# LLMs, Datasets, Local AI & Point Clouds - Link: https://eloquent-algorithmics.com/ - Published: 2024-03-04T16:36:05-05:00 - Author: ExplorerGT92 E/A Eloquent Algorithmics [ Home ](https://eloquent-algorithmics.com/) [ Services ](https://eloquent-algorithmics.com/services/) [ About ](https://eloquent-algorithmics.com/about/) [ Contact ](https://eloquent-algorithmics.com/contact-us/) APPLIED AI + DATA ENGINEERING # Custom AI.⏎ Local compute.Usable data. Turn domain knowledge and raw data into practical systems. Eloquent Algorithmics helps with custom LLMs, curated datasets, local AI hardware and setup, and raw point cloud processing. [ Discuss your project ↗ ](https://eloquent-algorithmics.com/contact-us/) [ Explore services → ](https://eloquent-algorithmics.com/services/) FROM RAW INPUT TO WORKING SYSTEM MODEL / DATA COMPUTE / GEOMETRY Four disciplines. One practical workflow. FOUR CONNECTED SERVICES ## Built around the work you need to do. Start with one service or connect several into a complete workflow. Each begins with your inputs, intended result, and operating constraints. 01 ### Custom LLM solutions Adapt language models to your documents, terminology, and tasks with retrieval, targeted fine-tuning, and practical evaluation. 02 ### Dataset engineering Prepare consistent, documented datasets for training, evaluation, and retrieval through cleaning, labeling, and quality checks. 03 ### Local LLM hardware & setup Plan and configure local AI compute around your models, workload, users, and budget— from hardware sizing to inference setup. 04 ### Raw point cloud processing Prepare raw LiDAR and 3D scan data for downstream work with filtering, alignment review, organization, and usable exports. [ Explore the full service scope → ](https://eloquent-algorithmics.com/services/) HOW THE WORK MOVES FORWARD ## A clear process. A result you can evaluate. Define the task, inspect representative data, and test a focused solution. Use the findings to guide deployment and a documented handoff. [ How we work → ](https://eloquent-algorithmics.com/about/) 01 / Define the task Agree on inputs, expected outputs, constraints, and the criteria used to judge the result. 02 / Inspect the data Review representative documents, records, or scans and identify gaps that affect the work. 03 / Build and evaluate Develop a focused workflow, test it on relevant examples, and document the findings. 04 / Deploy and hand over Configure the agreed environment and provide the process, settings, and notes needed to operate it. A PRACTICAL START ## Good questions.⏎ Clear starting points. A few things to consider before starting an LLM, dataset, local AI, or point cloud project. Do I need to train a language model from scratch? A project can often begin with an existing model, a retrieval workflow, or targeted fine-tuning. The choice depends on the task, available data, operating constraints, and evaluation results. What makes a dataset ready for use? Readiness depends on its purpose. Useful checks include consistent structure, clear labels, duplicate handling, representative evaluation data, and documented sources and limitations. These checks are defined for the intended workflow. How is local LLM hardware selected? Sizing starts with the model and workload: memory requirements, context length, concurrent users, response expectations, and budget. Hardware compatibility and runtime support are assessed together, then checked with representative requests. What information is needed for point cloud work? Start with a representative scan, its source format, capture details, units and coordinate information when available, and the output you need. These establish the processing steps and the appropriate quality checks. ## What would you like your data to do? Tell us about the task, the data you have, and where the solution needs to run. [ Start a conversation ↗ ](https://eloquent-algorithmics.com/contact-us/) Eloquent Algorithmics Custom LLMs. Datasets. Local AI. Raw point cloud processing. [ Services ](https://eloquent-algorithmics.com/services/) [ About ](https://eloquent-algorithmics.com/about/) [ Contact ](https://eloquent-algorithmics.com/contact-us/) [ Privacy policy ](https://eloquent-algorithmics.com/privacy/) START A CONVERSATION [ info@eloquent-algorithmics.com ](https://eloquent-algorithmics.com/info@eloquent-algorithmics.com) Atlanta, Georgia © 2026 Eloquent Algorithmics · Second Opinion Solutions LLC