SpikingAI Real Time AI Insights for Capital Markets

Institutional positioning is public information that almost nobody can read. SEC filings, block trades, options open interest, and unusual volume arrive in raw form across incompatible sources, and interpreting them requires specialist knowledge most investors do not have. Firms serving those investors face the same problem at scale: turning institutional activity into something a client can understand takes an analyst, and that analyst becomes the ceiling on how much market commentary the business can publish. Building an alternative in house means assembling market data ingestion, entity resolution, model orchestration, and a compliance safe output layer, typically six to twelve months of engineering before the first useful result.

SpikingAI provides that capability as a managed platform. It ingests SEC filings, block trade records, options chains, and open interest, normalizes them into a single entity resolved dataset, and resolves institutional holders across name variants and subsidiaries so positions aggregate to the actual owner rather than fragmenting across filings. Multi leg options positions are identified as coherent trades and mapped against a library of 56 defined options structures, showing what a position is built to do across price and volatility rather than only what was bought. Every derived figure traces back to its source record and timestamp, which is what allows generated commentary to be defended when a client or a regulator asks where a number came from. Foundation models running on Amazon Bedrock then generate the explanation layer: ranked activity summaries, structural interpretation of positioning, and plain language briefings written at configurable tone and reading level, available on demand or on a schedule. Access is through conversational AI, REST APIs, SDKs, and embeddable UI components, with coverage spanning equities, options, and digital assets.

All inference runs on Amazon Bedrock inside the buyer's AWS account and chosen region, so prompts, market data, and generated output remain within the buyer's environment and integrate with existing identity, logging, and billing controls. The architecture is model agnostic across Bedrock hosted foundation models, letting buyers select or switch models on cost, latency, or governance grounds without application changes. Brokerages and trading platforms use SpikingAI to add an AI research layer without building a data pipeline. Financial media and investor education businesses use it to widen instrument coverage and publishing frequency without adding research staff. Wealth platforms and family offices use it to bring institutional flow context into client conversations. Fintechs building investor facing products use it as the explanation layer their data already needed. Reporting that previously consumed several analyst hours per day is produced in minutes, and coverage scales with instruments rather than headcount.

SpikingAI is an educational and research tool. It does not provide investment advice, execute trades, or make performance representations.