Writing on private AI for hedge funds, RIAs, and family offices.

Practical writing on private, on-premise AI for hedge funds, registered investment advisers, and family offices: the compliance arguments, the hardware, and an honest account of what open-weight models do well. Written by William Dorman, Founder of Black Lily.

What an RIA Can Do With Lily Desk: The Two-Minute Tour: One working day at an advisory firm in two minutes: the morning filings digest, a client's holdings checked against their IPS, a white paper read page by page, a new stock's 10-Ks compared, a client project, the committee dashboard, the quarterly letter, and one search across all of it.
Lily Desk for RIAs in 30 Seconds: A Watchlist That Reads the Filings: Thirty seconds of Lily Desk, the research desk Black Lily installs on a server your firm owns: a ticker goes on the watchlist, its 10-K and 10-Q land in the library, and one plain-English request builds a dashboard for the investment committee.
Your MNPI Policy Already Rules Out Cloud AI: Section 204A requires written policies reasonably designed to prevent the misuse of material nonpublic information. Every prompt to a hosted model is a new path that material can travel, and a new control you have to write, test, and defend.
AI Prompts Are Business Records, and Most Firms Are Not Treating Them Like It: The SEC's off-channel communications cases have reached more than 100 firms and over two billion dollars in penalties since 2021, all over records that lived outside the systems the firm preserved. A chat window with a model is the same shape of problem.
What the 2024 Reg S-P Amendments Mean for Every AI Vendor You Add: The amended rule requires a written incident response program and customer notification within 30 days. Each outside service holding customer information is one more place an incident can start and one more notification you may have to make.
The AI Questions Allocators Now Ask in Operational Due Diligence: ODD teams have moved from asking whether you use AI to asking where the data goes. Here is what the questionnaire actually wants to know, and why an on-premise deployment turns most of it into a one-line answer.
A Research Desk, Not a Chat Window: A chat box has no memory of your firm's work, no project structure, nothing that runs overnight, and nothing to present from. Those absences are why AI pilots at small firms stall after the demo, and they are fixable.
Open-Weight vs Frontier: An Honest Account of What a Local Model Does Well: Open-weight models are genuinely behind the best hosted models at some things and genuinely competitive at others. The gap does not fall where most vendor material implies, and the difference decides whether a local deployment is worth buying.
What Machine Does a Private LLM Actually Need?: The honest version, with the numbers that matter: why VRAM sets the ceiling, why concurrency and not document count drives the spend, and why most small firms need one workstation rather than a rack.
The Family Office Document Problem Nobody Has Solved: Decades of trust instruments, entity charts, and manager reports, held by a staff small enough that everything depends on who remembers what. It is the clearest case for a searchable model and the hardest one to put in the cloud.
AI Washing: What the SEC's First Two Cases Mean for How You Describe Your Own AI Use: In March 2024 the SEC charged two advisers for saying they used AI in ways they did not. The lesson is not to stay quiet about AI. It is that the description has to match the deployment, which is easier when you can point at the machine.
How AI is Transforming Oilfield Operations: From automated field ticket processing to predictive well maintenance, AI is reshaping how operators manage daily workflows across the Permian Basin and beyond.
5 Signs Your Business Needs AI Integration: Still relying on spreadsheets and manual data entry? Here are the clearest indicators that your operation is ready for intelligent automation.
Predictive Maintenance: Reducing Downtime by 40%: How machine learning models trained on sensor and inspection data are helping service companies prevent equipment failures before they happen.
The Real Cost of Manual Data Entry in Oil & Gas: We break down the hidden costs of paper-based workflows, from labor hours and error rates to delayed invoicing and compliance risk.
Building Production-Ready AI Systems: Our Approach: A look inside our engineering process, from scoping and data audit through deployment, monitoring, and team training.
Black Lily vs. Deloitte for AI Automation: Deloitte is a global consulting giant with a massive AI practice. But for a Permian Basin service company that needs working automation, not a strategy document, the fit is wrong.
Black Lily vs. Accenture for AI Automation: Accenture serves BP, Shell, and Saudi Aramco. If your company has 50 employees and a manual invoicing process, their model does not scale down to you.
Black Lily vs. McKinsey Digital (QuantumBlack) for AI Automation: McKinsey delivers AI strategy decks for C-suite executives. Black Lily builds the actual system and makes it run. Here is why that distinction matters for your business.
Black Lily vs. Zapier for Business Automation: Zapier connects SaaS apps with pre-built integrations. But for oilfield operations with legacy systems, custom data pipelines, and AI workflows, it was not designed for your problem.
Black Lily vs. Make.com for Business Automation: Make.com offers powerful visual workflow building for technical users. But without discovery, training, or ongoing support, it leaves oil and gas companies on their own.
Black Lily vs. C3.ai for Oil and Gas AI: C3.ai builds enterprise AI applications for billion-dollar energy companies with data science teams and IT departments. If that is not you, here is why Black Lily is the better fit.
Black Lily vs. SLB Delfi for Oil and Gas AI: SLB Delfi is a digital platform for reservoir modeling and production analytics. If you are an OFS company trying to automate field operations, Delfi is solving a completely different problem.
Black Lily vs. Upwork Freelancers for AI Automation: Freelancers on Upwork and Fiverr can build fast and cheap. But when the system breaks six months later and there is no one to call, the real cost becomes clear.
Black Lily AI vs. Traditional SCADA: Where Intelligent Automation Starts: SCADA systems handle real-time control and monitoring. Black Lily sits on top, turning the operational data your SCADA already collects into automated workflows, reports, and business intelligence.
Using Black Lily AI with Allen-Bradley PLCs: Allen-Bradley PLCs from Rockwell Automation are everywhere in Permian Basin operations. Black Lily connects to the data they produce to automate reporting, maintenance workflows, and operational intelligence.
Black Lily + Compressor Skid Controls: Automating Beyond the PLC: Your compressor skid controls handle the process. Black Lily automates everything above them, from runtime reporting and predictive maintenance to automated dispatch and compliance documentation.
Black Lily AI for Upstream Operations: Well-Site Automation and Production Optimization: Lease operators, pumpers, and production teams in the Permian Basin are drowning in manual reporting. Black Lily automates production data capture, artificial lift monitoring, and TRRC compliance reporting directly from your well-site infrastructure.
Black Lily AI for Midstream Operations: Compression, Gathering, and Gas Processing Optimization: Midstream operators manage compressors, gathering lines, and gas plants across the Permian Basin. Black Lily automates throughput optimization, compressor fleet predictive maintenance, and custody transfer reconciliation from data your systems already collect.
Black Lily AI for Downstream Operations: Terminal Automation, Blending Optimization, and Distribution Intelligence: Downstream operators managing terminals, blending operations, and fuel distribution are sitting on process data that could automate scheduling, optimize blending ratios, and eliminate manual BOL processing. Black Lily builds that automation layer.

About Black Lily

Black Lily installs private AI on a server in your office for hedge funds, registered investment advisers, and family offices, so your documents and prompts never leave your network. We size the hardware, install it, and maintain it. Separately, we turn paper, handwriting, and inconsistent spreadsheets into structured data your systems can import. Founded by William Dorman, Founder & CEO.

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