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ixprt Research
Research Collective, ixprt
ixprt Research is the collective byline for posts published by ixprt without a single named author. Posts cover industry analysis, vendor evaluations, and benchmarks across data-for-AI, quant infrastructure, and AI-generated market research.
Posts
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Industry Report ixprt Research
Can AI Write Equity Research? The 2026 State of the Art
AI can draft the mechanical layers of equity research in 2026: earnings recaps, filing summaries, and estimate updates grounded in ingested documents. Thesis origination, accountability, and judgment calls remain human work.
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Comparison ixprt Research
Kalshi vs Polymarket: How the Two Prediction Markets Actually Compare in 2026
A 2026 side-by-side of Kalshi and Polymarket: regulatory standing, liquidity by category, fee structures, contract design, and where each one is brittle.
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Buying Guide ixprt Research
RAG Chunking Strategies in 2026: A Practical Field Guide
A chunking strategy is the rule that divides documents into the units a RAG system embeds and retrieves. The 2026 field narrows to six practical approaches: fixed-size windows, structure-aware recursive splitting, semantic splits, late chunking, parent-document retrieval, and LLM-derived propositions, chosen by document type and budget.
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Comparison ixprt Research
Reranking in RAG Pipelines: When Cross-Encoders Pay Off
Reranking adds a second scoring pass to a RAG pipeline: a cross-encoder rescores the retriever's top candidates so the best chunks reach the model's context window. It earns its latency once the correct document reliably lands in the top 50 results but outside the top 5.
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Industry Report ixprt Research
AI Agent Memory Architectures: How Persistent Memory Actually Works
The four patterns for giving AI agents persistent memory in 2026, the specific systems shipping each one (Letta, Mem0, OpenAI, Claude), and the recall-fidelity vs token-cost tradeoff every team eventually confronts.
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Buying Guide ixprt Research
How to Evaluate RAG Pipelines
A 2026 buyer's guide to RAG evaluation: the three eval families, the metrics that actually predict production quality, the four major frameworks (Ragas, TruLens, ARES, DeepEval) compared, and which one to start with depending on where the pipeline is in its lifecycle.
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Industry Report ixprt Research
The State of AI in Finance: 2026 Benchmark
Where AI sits in finance in 2026 — data infrastructure adoption, quant integration, AI-generated equity research market, regulatory framing, and a 12-month outlook.
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