Investors, Advisors, Traders -- amgtoken.com launched 10/1/2026: amgtoken.com Select "Demo"
SLM: The amgtoken.com site is a platform with two profit engines that are scaffolded to operate an agentic proprietary server of 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; EDGAR 100% accuracy; stable static context. The SLM dual-vector prefilled integer kernel reduces token spend with the reusable and prewarmed-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.
Users must be customers of an NASD brokerage to Train any LLM Researching Unexplored 30+ years of True Investor Sentiment Data and Interactive Analytics in the AMG Kernel. Code can be made Available in a private GitHub repository or Lovable Cloud for appended downloads to Train LLM with the continuous Fund Flow data your broker is already receiving from LSEG, FactSet, and Morningstar along with continuous updates of Quarterly 13F and Monthly N-PORT EDGAR Holdings data. The list of Fiduciaries below value this information.
Scope -> Advise/Consult/Prompt/License Established Data + Analytics dedicated team for developed code and training products is Completed. Bid Wanted 1-100% 10,000,000 California Sub S shares.
The system uses the Model Context Protocol to host a private MCP server of market data that maximizes cache efficiency (reduce costs) in front of an LLM request. The outcome is to transform a simple non-reasoning dual-vector 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, Perplexity, ThomsonReutersAI....©2026 Robert Adler, All Rights Reserved
Interactive dashboard controls facilitate opportunities to research shared 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.
Demo: Prototype dashboard visualization templates to train unique LLM signals using continuous market data overlays of changing regulated values and sentiment.
Founding research and equity offering extends to Regulated Information Customers who purchased Open-end Fund Flow and Securities Ownership data, and renewed subscriptions to the information during the 2010 sale of AMG Data Services to Thomson Reuters (now LSEG):
Bank of America
Goldman Sachs
Renaissance Technologies
Fidelity Management & Research
Barclays Capital
JP Morgan Chase
Daiwa
Citigroup
Credit Suisse
Leuthold Weeden
Viking Global
UBS
SG Americas
Thomas Weisel Partners
Standard & Poor's
Relevant:
NASDAQ - Membership
Newscorp - Text & Fox
AWS - Cloud Data Services
Lyft/Uber (Rideshare model for less regulated and non-Financial dimensional templates)
....