US Government Contract Awards Monitor: Federal Wins, Momentum and Agency Concentration

Turn raw federal procurement data into a clean government contracts signal: recent wins per company, total award momentum, agency concentration and the largest new awards, scored and ranked. Give one or more company or recipient names and this Actor pulls their recent US federal contract awards from the official USAspending.gov API. Instead of a flat list of award rows, you get a per-company view built for research: how much new federal money a company is winning, which agency is buying, and which fresh wins are the biggest. It is alternative data for traders, quants, and competitive intelligence teams who treat federal revenue as an early demand signal.

Why this is different

Several scrapers return raw USAspending award rows. This Actor is not one of them. It computes a signal layer on top of the same official data so you do not have to.

• Scored momentum, not a raw dump. Each award gets an impact score from 0 to 100 based on size plus recency, and awards are ranked so the largest, freshest federal wins surface first.
• Recent wins only. The query uses the USAspending new_awards_only date type, so you see contracts newly signed inside your look-back window. Old megacontracts that merely had a recent modification are excluded.
• Momentum per company. Every company returns a total recent award value and an award count, plus a count of high-value ($10M and above) wins.
• Agency concentration. The Actor aggregates award value by awarding agency and reports the single biggest buyer per company, so you can see who is funding the revenue.
• Verifiable. Every award carries a direct link to its USAspending.gov page, so any number traces back to the official source.

Who it's for

• Traders, quants and portfolio managers who treat federal contract revenue as an early demand signal and want a ready-made government contracts feed for screening and research rather than a manual USAspending search.
• Competitive intelligence and business development teams who track who is winning in their market, from which agency, and how recent and large those defense contracts and civilian awards are.
• Fintech and research apps that want to drop structured contract-win data into a product, dashboard, or model without maintaining a USAspending integration.

Use cases

• Federal-revenue screening. Run a watchlist of contractors and rank them by recent award momentum to spot which names are accelerating.
• Defense and govcon coverage. Monitor defense contractors for large new Department of Defense task orders and see how concentrated their wins are in one agency.
• Event and catalyst research. Flag a large, recent federal win on a company you follow and trace it to the exact award before it reaches headlines.
• Business development intelligence. Track competitors and partners to see which agencies are awarding work in your space and at what size.
• Watchlist monitoring. Schedule recurring runs so a new high-impact award on any tracked company is captured automatically.

Input

Field	Type	Required	Default	Description
companies	array	yes	-	One or more company or recipient names (for example Palantir, Lockheed Martin, Booz Allen). Each is scanned for recent federal contract awards.
sinceDays	integer	no	365	Look-back window in days. Only contracts newly awarded within this many days are counted (7 to 1095).
maxAwards	integer	no	25	How many of the company's largest recent awards to return and rank per company (1 to 100).
minImpact	integer	no	0	Only return awards at or above this impact score, 0 to 100. For example 85 keeps roughly $100M and larger recent wins. 0 returns all.

Output

The Actor pushes one item per company: the query, total recent award value, award count, a high-value ($10M and above) count, the top agency by value, and a ranked list of awards. Every award includes the recipient, amount, awarding agency and sub-agency, start date, description, award ID and type, the impact score, a short catalyst string, and a direct USAspending.gov URL.

{
  "type": "gov_contracts",
  "query": "Palantir",
  "total_recent_value": 744000000.0,
  "award_count": 12,
  "high_value_count": 5,
  "top_agency": "Department of Defense",
  "awards": [
    {
      "recipient": "PALANTIR USG, INC.",
      "amount": 293000000.0,
      "agency": "Department of Defense",
      "sub_agency": "Department of the Army",
      "start_date": "2026-03-14",
      "description": "DATA PLATFORM AND ANALYTICS SERVICES",
      "award_id": "W912CG26F0001",
      "award_type": "DEFINITIVE CONTRACT",
      "impact": 95,
      "catalyst": "$293,000,000 contract from Department of Defense",
      "url": "https://www.usaspending.gov/award/CONT_AWD_W912CG26F0001"
    }
  ]
}

Amounts and example values above illustrate the schema. Live values come straight from USAspending.gov at run time.

How the score works

The impact score is transparent and computed only from award size and recency.

• Size band sets the base. $1B and above scores 95. $100M to $1B scores 85. $10M to $100M scores 70. $1M to $10M scores 55. Below $1M scores 40.
• Recency adds a bonus. If the award start date is within the last 90 days, add 10; within the last 365 days, add 5. The total is capped at 100.

Awards are then sorted by impact, highest first, so the largest and most recent government contracts rank at the top. There is no hidden input and no model: the same award always produces the same score.

Use with AI agents and automation

This Actor returns clean JSON on demand or on a schedule, which makes it easy to wire into agents and automation.

• AI agents and frameworks. Call it from LangChain or LlamaIndex as a tool, or expose it through the Apify MCP server so an assistant such as Claude, ChatGPT, or Cursor can run it and read the results directly.
• No-code automation. Route output through Zapier or Make to a spreadsheet, database, or alert channel.
• Webhooks. Fire a webhook on run completion to push fresh contract-win data into your own systems.
• On demand or scheduled. Run it ad hoc, or schedule recurring runs to keep a watchlist monitored.

Pricing

This Actor uses pay-per-event pricing: one charge per company analyzed, billed as the company-analyzed event. Scanning a 10-company watchlist is 10 charges. There is no subscription and no monthly minimum, so you pay only for the companies you actually scan.

Data source and compliance

All data comes from the official USAspending.gov API operated by the US Treasury under the DATA Act. It is public federal spending data, served over REST and JSON with no API key required. The Actor reads award records about organizations and federal agencies, not individuals: it does not collect or process personal data, and every award links back to its official USAspending.gov page so the source is fully auditable.

FAQ

Where does the data come from? USAspending.gov, the official US Treasury source for federal spending mandated by the DATA Act. The Actor uses the public API with no key required.

What counts as a recent win? The query uses the new_awards_only date type, so only contracts newly signed inside your sinceDays window are returned. Old contracts with a recent modification are excluded.

Does a contract win guarantee revenue? No. It signals awarded federal money; recognized revenue depends on execution and timing, so treat it as a signal, not a certainty.

How current is the data? USAspending is updated continuously, and each run reads the latest awards available at that moment.

Can an AI agent call this automatically? Yes. Expose it through the Apify MCP server and an AI agent such as Claude, ChatGPT, or Cursor can invoke it on its own and read the JSON output. It also works as a LangChain or LlamaIndex tool.

How am I charged? Per company analyzed. One company in your input is one charge, with no subscription.

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Keywords: government contracts, federal contract awards, USAspending API, govcon, defense contracts, government spending data, contract win signal, federal procurement, BD intelligence, alternative data, contractor revenue signal.

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Note: Provided as data for research, screening and monitoring, not investment advice. Historical patterns do not guarantee future results.