Platform Agent — Opus
Bruno.Intelligence synthesis.
Dozens of signal sources. One daily brief. Alpha-Alpha aggregates regulatory filings, executive movements, funding rounds, industry news, social chatter, and government contracts into structured intelligence — delivered before you've finished your coffee.
The Problem
The signals exist. Nobody has time to find them.
Every business decision depends on information that's already public — buried across RSS feeds, government databases, job boards, news sites, social platforms, and regulatory filings. The problem isn't access. It's aggregation.
A competitor files for a new patent. A key prospect posts a job listing for the exact role your product replaces. A regulatory change creates urgency in three of your target industries. A government contract opportunity drops on USAspending.gov with a 14-day window. A prospect's CEO posts on LinkedIn about the exact pain point you solve.
Each of these is a buying signal. Each is publicly available. And each is invisible to you unless someone is actively monitoring every source, every day, and synthesizing what it means for your specific business.
No human team can monitor 80+ industry sectors, dozens of RSS feeds, multiple social platforms, regulatory databases, and government contract portals simultaneously. Not manually. Not sustainably. Alpha-Alpha does this on a schedule, automatically, and delivers the synthesis — not the raw data — as a structured brief.
How It Works
Collect. Filter. Synthesize. Deliver.
Alpha-Alpha runs a four-stage pipeline that transforms raw signal noise into actionable intelligence.
Multiple collectors run on independent schedules, each covering a different signal category. Event-based collectors scan for executive appointments, labor disruptions, and franchise expansions. Regulatory collectors monitor the Federal Register for rule changes affecting target industries. Budget collectors track government contract opportunities and spending patterns. Social collectors scan platforms for relevant conversations, pain points, and market chatter. RSS collectors aggregate industry publications across dozens of feeds. Each collector outputs structured signal records to a central staging area.
Raw signals pass through a multi-layer filter. A media blocklist removes press releases, aggregator republishes, and promotional content masquerading as news. Industry classification maps each signal to a specific sector using a rotating taxonomy that covers 80+ NAICS codes over a 40-day cycle. Relevance scoring weights signals by type — executive changes and labor crises score highest because they correlate most strongly with buying intent. Low-confidence signals are flagged rather than discarded, preserving weak signals that may strengthen with corroboration.
Filtered signals are aggregated and cross-referenced. A regulatory change in one sector is linked to a related executive appointment in a company in that sector. A government contract opportunity is connected to a prospect already in the pipeline. The synthesis layer produces a structured brief — not a list of raw signals, but an analysis of what they mean, which ones demand attention, and what actions they suggest. Briefs are generated using high-reasoning models for the synthesis layer, ensuring the connections drawn are substantive, not superficial.
Completed briefs are delivered on schedule — typically daily, with weekly rollups for pattern recognition. Delivery channels are configurable: messaging apps, dashboards, email, or direct integration into CRM systems. Each brief includes signal sources, confidence levels, and recommended next actions. The delivery is the only part most users ever see. Everything upstream — collection, filtering, synthesis — runs autonomously.
Signal source categories
Executive Movements
New hires, departures, promotions at target accounts and competitors
Regulatory Changes
Federal Register filings, compliance deadlines, new rules by industry
Government Contracts
USAspending.gov opportunities, award data, budget allocations
Industry Publications
30+ RSS feeds across supply chain, HR, healthcare, finance, and more
Social & Community
Reddit threads, LinkedIn posts, forum discussions signaling pain points
Competitor Activity
Product launches, pricing changes, hiring patterns, positioning shifts
The OS Underneath
Intelligence that compounds over time.
Alpha-Alpha doesn't just collect signals — it remembers them.
The memory layer tracks which signals were acted on and which were ignored. Over time, this creates an implicit relevance model: the agent learns which signal types generate action for your specific business. A regulatory filing that drives outreach for one company is noise for another. The agent adapts.
Verification gates ensure that signals are attributed correctly. A headline about "Company X hires new CTO" is verified against the source before being included in a brief. Media blocklists prevent press releases and promotional content from being treated as independent signals. Cross-referencing catches duplicate signals reported by multiple sources, preventing artificial amplification.
Fleet learning means that signal patterns discovered in one deployment improve filtering across the fleet. If a new type of noise source is identified in one client's feed — say, a blog that republishes press releases as original content — that source is flagged across all deployments that share the same feed category.
Model: Opus — chosen for the synthesis layer because cross-source intelligence correlation requires deep reasoning, not just extraction. Collection and filtering use lighter models for throughput.
Ready to see what an agent looks like for your workflow?
Your competitors' public signals are already out there. The question is whether you see them first. Alpha-Alpha builds the intelligence layer that runs before your team arrives in the morning.
Let's TalkFixed price. Two to four weeks. You own the code.