External Signal Intelligence for Competitive and Regulatory Monitoring
Your competitors file patents. Regulators publish enforcement actions. News breaks about supply chain disruptions. Financial disclosures reveal strategic shifts. All of this is public — but no single person can track it across every source that matters. Surveil ingests news, regulatory filings, patent data, and financial disclosures into a unified pipeline, applies AI to resolve entities and detect competitive signals, and delivers structured intelligence your team can act on — not a pile of links to read.
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Ingest structured and unstructured data from news APIs, regulatory filing systems (SEC EDGAR, SEDAR+), patent databases (USPTO, WIPO), and financial disclosure repositories. Every document is normalized into a unified schema with full provenance — source URL, timestamp, content hash, and extraction confidence.
Resolve companies, people, and organizations across sources — the same competitor mentioned in a regulatory filing, a news article, and a patent application is recognized as a single entity. AI correlates signals across sources and timelines to surface relationships no single document would reveal.
Detect product launches, leadership changes, partnership announcements, regulatory actions, and financial events from ingested documents. NLP models trained on business event taxonomies classify signals by type, confidence, and competitive relevance — and surface them as structured alerts, not raw headlines.
Track how companies, products, and industry topics are discussed across news and analyst coverage over time. Detect statistically significant shifts in sentiment or narrative framing — positive or negative — before they are reflected in market reaction or competitor response.
Generate competitive landscape reports, market intelligence briefings, and risk assessments assembled from the full ingested corpus — not manually stitched from Google Alerts and search results. Delivered on a defined cadence with full source traceability on every insight. Export to PDF, CSV, or structured API feed.
Deploy agents that continuously scan ingested sources for signals of competitive activity — product launches, leadership transitions, partnership announcements, facility changes — and surface them as structured alerts with the underlying source documents attached.
Configure agents that watch regulatory filing systems and enforcement databases for proposed rules, final regulations, and enforcement actions that affect your industry or named counterparties — with structured impact analysis mapped to relevant entities in your watchlist.
Define agents that assemble competitive briefings, regulatory watch summaries, and market landscape reports on a defined schedule — pulling from the full ingested corpus, applying entity resolution, and distributing structured output to stakeholders without manual assembly.
Most competitive intelligence teams operate with Google Alerts, keyword searches, and a shared spreadsheet. Analysts spend the majority of their time finding data — scanning news sites, checking regulatory dockets, searching patent databases — and what remains for actual analysis is precious little. Signals are missed because no single person can check every source every day.
A competitor files a patent that signals a new product direction. A regulatory body proposes a rule that will reshape compliance obligations. A key supplier discloses financial distress in a filing your team does not routinely check. These are not edge cases — they are the daily reality of intelligence gathering that depends on manual search.
Adding headcount does not solve the structural problem. The volume of public filings, news, and patent activity grows faster than any team can scale. The answer is systematic ingestion, automated entity resolution, and AI-powered signal detection — the same architectural approach that powers intelligence platforms in the government sector, applied to enterprise competitive intelligence.
Surveil ingests news, regulatory filings, patent data, and financial disclosures into a single pipeline. Entity resolution connects mentions of the same organization across sources and time. Signal detection surfaces competitive events, regulatory changes, and narrative shifts as structured intelligence — not as a list of URLs. All models run locally. No data is sent to third-party AI services.
Surveil is designed for organizations where external awareness — competitive activity, regulatory developments, market shifts — is not a nice-to-have. Where missing a public signal has real operational or financial cost.
Strategy teams that need a systematic view of competitive activity, patent filings, leadership changes, and market positioning — not a weekly roundup of Google Alerts. Surveil replaces manual monitoring with automated ingestion, entity resolution, and signal detection that gives your team an actual information advantage.
Investment analysts and research teams that need to surface signals from unstructured public data — regulatory filings, news coverage, patent activity — before they are reflected in market pricing or structured data feeds. Automated ingestion and entity resolution mean you spend time on analysis, not collection.
Compliance functions that need to monitor regulatory developments, enforcement actions, and policy changes across agencies and jurisdictions — with structured impact analysis mapped to the specific entities, products, and operations they affect. Automated tracking replaces manual docket-checking.
Surveil is built on a modular architecture that separates ingestion, entity resolution, signal detection, and intelligence generation into independent layers. The ingestion layer connects to news APIs, regulatory filing systems (SEC EDGAR, SEDAR+), patent databases (USPTO bulk data, WIPO PATENTSCOPE), and financial disclosure repositories — with rate limiting, pagination handling, and schema normalization per source.
Every ingested document is normalized into a unified schema with full provenance: source URL, crawl timestamp, content hash, extraction confidence, and credibility metadata. The entity resolution layer maps companies, people, and organizations across sources using a combination of deterministic matching (legal names, tickers, registration numbers) and embedding-based fuzzy resolution for mentions that use variants or abbreviations.
The signal detection layer applies classification models to identify business events — product launches, leadership changes, partnerships, regulatory actions, financial disclosures — and ranks them by competitive relevance, source credibility, and recency. Sentiment and narrative tracking models monitor topic trajectories over time, surfacing statistically significant shifts as they emerge. All models run locally. No data is transmitted to third-party AI services.
Intelligence generation assembles structured reports, competitive briefings, and regulatory watch summaries from detected signals and the underlying source corpus. Every insight carries full data lineage — traceable to the specific document, timestamp, and processing path that produced it. Deployment options include Canadian cloud (Azure Canada Central, AWS ca-central-1) and on-premise for organizations with data residency requirements.
Surveil is currently in MVP development with an initial focus on news, regulatory filings, patent data, and financial disclosures. We are working with design partners to define the source integrations and signal taxonomies. If your team depends on external intelligence that currently runs on manual search — bring us your requirements.
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