Robert Adler - American Model Generator

RobertAdler@amgkernel.com

Seed: amgkernel.app

www.amgkernel.com

SLM A: amgtoken.com and amgtokenbroker.com operates an agentic proprietary server of changing numerically reconciled EDGAR financial sentiment values. The Small Language Model maximizes cache efficiency at the onset of the AI chatbot or agentic request by optimizing the TTFT gap with prefilled time-series analytics of integer data changes in continuous filings of market asset levels and flows; 100% accuracy; stable static context. The SLM dual-vector prefilled integer kernel additionally reduces token spend with the reusable cached request repository at the organization level. Customer ROI increases as the bidirectional MCP server evaluates call and token requests, and applies the output to select the most cost-effective LLM for the customer. The SLM filters AI output price/million tokens with non-reasoning cached tokens to mitigate complexity, bias, and bloated code that cause unnecessary token energy in a LLM request.

SLM B: amgkernel.com and amgkernel.app shelters Section 28(e) Research to operate organization-specific Fiduciary projects; and to best engage their customers fixated on identifying shared opportunities originating from changing values in the $70+ Trillion continuous EDGAR market data array of regulated filings.

• The American Model Generator empowers users to gain actionable intelligence about changing sentiment in any measured topic.
• The agentic operating system uses the Model Context Protocol to host a private server of market data to transform a simple dual-vector non-reasoning kernel of EDGAR filings into a powerful agentic orchestrator, that anchors and extends reasoning capabilities in MCP client LLM's without redesigning a core model, like Gemini, Claude, ChatGPT....
• Interactive dashboard controls facilitate research of questions and common understandings between the Fiduciary and Customer that are always fixated on their shared tangible form of expression: Trusted numerically reconciled values to anchor and extend a continuous learning awareness of how intentional sentiment is changing.
• The sentiment data analytics replicate Financial data templates of continuous open-end fund (incl. ETF) market asset vectors of intentional change in professional investor portfolio price level and flow data, and net investment flow metadata to visualize how values and sentiment are changing.
• Consult/Prompt/License/Launch SLM to train Financial (and non-Financial) opportunities for Fiduciaries and Customers that structure 'truth to value' signals about how intentional and actionable sentiment is changing.
• amgkernel.app Slide 4 visualizes the output of open-end Fund Flow (including ETF) action using updates LSEG sells. LSEG data can be appended to scaffolding for a nominal cost. Slide 5 scaffolding of 13F Holdings (>$100 million TNA) and N-PORT Mutual Fund and ETF continuous historical data is current 6/30/26.

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Thomson Reuters 2009-2010 Director Fixed Income Americas

• Sold AMG Data Services to Thomson Reuters (now LSEG)
• Upgraded Customer Subscriptions; 92% Renewal; Added new business globally.
• Managed the transition of the AMG fund flow and portfolio data acquisition systems, procedures, and methodologies.
• Integrated AMG products and pricing mechanisms to enhance the brand and product offerings.
• Research, Sales Closer with TR teams;
• Sourced media analysis of weekly fund flow data and reports to WSJ, Barron's, NY Times, Dow Jones, Bloomberg.

AMG Data Services ∙ 1991-2009     
Founder, CEO

• Designed, managed, and marketed accurate, timely, and comprehensive fund flow investment data as the weekly proxy for investor sentiment.
• Continuous subscription renewals to the AMG data by investment firms include Goldman, BAML, Citi, Fidelity, Renaissance, JP Morgan, Barclays, ....  
  
• Utilized evolving open-source database and Internet technologies to collect, verify, and train asset and price data into reports of investor fund flows in the $45+ Trillion US mutual fund (incl. ETF) data set.
• Created database of SEC investment management companies and US registered mutual fund portfolios to dimensionalize relative liquidity in industry groups, countries, ETF classes, and other indexes structured for emerging analytics of security-specific portfolio datasets.

Bridge Information Systems ∙ 1986-1989
Director of Fixed Income
Designed and marketed a fixed income order indication system to >100 dealers and investment managers that enabled market participants to indicate bond purchase/sale interest with specific/vague ID of the price, size, and name components of a securities trade.

Robert L. Adler & Co, Inc. ∙ 1982-1986
Founder, CEO

• General securities broker dealer was granted a 'No-Action letter' by SEC Staff to operate a tax-exempt securities exchange. 
• The automated execution system for municipal bonds was among the first fixed-income trading systems developed and implemented in a regulated environment.
  

Securities and Information Industry Positions 1968-1981 include:

• Municipal Bond Trading, Underwriting, Sales
• Corporate Planning
• Tax Shelter Sales
• Cage Operations

EDUCATION - TRAINING

New York University (Stern) Graduate School of Business Administration:

• MBA - Management Science

University of Minnesota:

• Bachelor of Arts – American Studies, Sociology, Chemistry

NASD Examinations (CRD License 1645):
S1: Full Registration/General Securities Representative
S24: General Securities Principal
S27: Financial and Operations Principal
S53: Municipal Bond Securities Principal

Lectured in Money, Banking, Corporation Finance
California State University (Humboldt)