Context Analytics, Inc. (CA)

In today’s volatile market, understanding how themes like tariffs and trade wars impact companies is essential. Context Analytics’ ThemeXplorer tool uncovers real-time trends in SEC filings and earnings calls, helping investors identify risk exposure and sector impact fast. Click the link below to read! #trade #themexplorer #risks #tariff #topicmodeling #recession #inflation #unstructureddata #textualdata #secfilings #earningscall #transcripts #energy #crudeoil #gas #consumablefuel $PARR $NRP $NOA #trends #sentiment  #portfolio #corporatedisclosures #tradewar

The story of today’s market is written in sentiment. Here are the tickers making moves—watch the video for the full picture (9/26/25). $PCAR $CRNX $GUTS $AMPY $FSFG $COST $PPTA $AXON $BULL $USAR $CNXC $RH $KMX $W $RIG $AQST $IBKR $MSTR $DVLT $NUAI $GUTS $INTC $CIFR $CVNA $SPRC $LAC $CIFR $ASPU $HFWA $HROW $SPCR $AXON $TITP #MarketSentiment #InvestorInsights #Equities #StockMarket

Is today’s market leaning more confident or more cautious? Today's Starting Line Sentiment Scan reveals the shifts behind investor behavior (9/25/25). $BTOC $SFIX $DXF $WS $BB $NAK $JBL $MOS $ACN $RIO $KMX $FCX $KBH $DELL $HRMY $F $UPST $ACAD $RBLX $ALAB $TNFA $LAC $QURE $CLPT $OPEN $IREN $PSQH $ATCH $HTZ $JD $IAS $CIFR $LAC $QURE $AXON $ACN $FSS #MarketSentiment #InvestorInsights #Equities #StockMarket

Hallucinations don’t belong in financial data. 🛑 Missed the Data Management Summit: New York last week? Our CEO, Joe Gits of Context Analytics, shared how to make LLMs accurate, reliable, and audit-ready — turning AI risk into opportunity. 👉 Watch the full keynote below #AI #FinTech #DataManagement #AgenticAI #AITrust #FinancialData #Innovation #DMSNY #LLM #LargeLanguageModel #DataIntegrity

Confidence climbs in select names while pressure builds elsewhere—today’s sentiment breakdown. Here's today scan results (9/24/25): $SHFS $MLKN $LAC $IAS $THO $CLPT $SAVA $PENN $NOW $CTAS $ACAD $SLNO $BYND $FCX $HD $STLA $RDDT $FLY $LAC $ASTS $RKLB $PLUG $HOLO $GLTO #Fintech #Investing #Trading #Signals

Markets never stop talking. September 22 sentiment reveals the stories of confidence and caution behind today’s trading activity. $QLGN $MSTR $HOUS $MBX $BOXL $PFE $SNAP $FFAI $BKKT $ASTS $AMC $KVUE $GLXY $COST $BE $NFLX $HUT $OPEN $BOXL $BIO $QLGN $PFE $MBX $SMLR $VKTX $ETHZ #innovation #digitalbanking #fintechnews

Thank you Data Management Insight, from A-Team Group! We’re grateful for the opportunity for our team and CEO, Joe Gits, to join a panel and deliver a keynote at this year’s Data Management Summit New York. It was inspiring to connect with so many leaders across the data and investment ecosystem and showcase how Context Analytics is helping firms adopt AI with confidence. Joe’s keynote, “From Risk to Opportunity – Minimizing Hallucinations in Financial Data,” explored the power of LLMs and how to unlock their potential without the risk. Key takeaways: • Predictive alpha lives in unstructured data • Traditional LLMs can hallucinate — creating risk in financial workflows • Our Agentic AI pairs LLMs with curated, verified data for accuracy and explainability • Purpose-built for financial professionals: domain-specific, compliant, and auditable • Firms can accelerate AI adoption without sacrificing trust or data integrity Thanks again to the A-Team Group for bringing together such an engaged and forward-thinking community! #DataManagement #AI #FinancialData #AgenticAI #DMSNYC #datamanagement #data #ai #genai #llms #hallucinations #dataquality #governance #unstructureddata

Thoughts from our panel discussion on how to ensure high quality and trusted data for AI, at Data Management Summit New York: -Moving from reactive /rules based to pro-active -Apply AI across the DQ process - not necessarily replacing existing rues but augmenting - AI helps with proactive Managing Unstructured Data: -Growth & opportunity but the risks is higher -Historical tools are focused on structured data -Unstructured Quality KPIs - lineage is key -Ensure vendors meet formatting standards -we're still early in the Unstructured data quality journey -Raw document to JSON - enables applying traditional DQ rules Automating unstructured remediation at scale? -Agentic AI can flag - automate the fix - then test that the fix is valid - what's missing? First step - Structure the data - by transforming into JSON - then apply analytics -e.g. Take 50 records for manual assessment - apply AI and compare how it performed - Human in the Loop is always necessary Key org challenge for establishing the Ground truth: -Used to be 100% correct before data hit production - we're now probability based meaning 90% of the data is correct going into prod - creating greater oversight challenges so demands Probabilistic tools are great for probabilistic answers - not for 100% accuracy Using AI to streamline data management: -dealing with scale -identifying missing / incomplete data -detecting issues earlier in the pipeline A governance framework can fail if everyone interprets and executes differently - essentially creating multiple frameworks If governance slows you down, it's a cost center, if it's keeping you safe, it's an asset - Does a speed limit slow you down or keep you safe? Where AI should NOT be used: -Where bias in data -Don't use AI where you need a believable answer -Critical decision making Think of it as an excellent assistant Implementing new DQ monitoring and observability tools tops Priority actions Key takeaways: -Culture -Trust framework -Governance model - we have new tools but the good data management skillset is probably more important than ever - we can do it at scale and faster #DMSNYC #datamanagement #data #AI #GenAI #LLMs #dataquality #governance #unstructureddata BNY SMBC Group Datactics Informatica Context Analytics, Inc. (CA) Brian Greenberg Manal Alimari Eugene Coakley, OLY Amy Horowitz Joe Gits, CFA

Takeaways from Joe Gits, CFA keynote discussion 'From risk to opportunity – minimizing hallucinations in financial data' at Data Management Summit New York: -There is predictive alpha in unstructured data ... -Hallucination stems from their fundamental design - they're trying to guess the next word Define Role & Scope Anchor with Content - narrow LLM to the data it's given - ignore ALL prior training Organized instructions Enforce the output schema Add fallbacks - Explicitly instruct - if insufficient context, return "INSUFFICENT_CONTEXT" Prompt engineering: Carefully crafting prompts to provide more context and guidance to the LLM - define at a granular level exactly what is required AI creating its own AI - e.g. Claude Code #DMSNYC #datamanagement #data #hallucinations #AI #unstructureddata #LLMs #promptengineering Context Analytics, Inc. (CA)

Headlines overwhelm. Context Analytics filters the market mood. September 19 sentiment shows where conviction is building—and where caution is creeping in. (9/19/25) $TIC $XXII $CDLX $AGMH $AIIO $METC $STRL $CJET $SES $SKYT $SCHL $REPL $LEN $LEN.B $FDS $DIS $SPGI $RVPH $BINI $LWAY $INTC $ADAP $AGMH $AERT $DVTL $CLSK $CDLX $COIN $SOFI $AMD $CJET $MSTR #FinTwitt #shortsqueeze #dataengineering