Tender Change Monitor v2

Convert tender change v2 inputs into structured procurement intelligence with extracted fields, classifications, changes, and source evidence.

What this Actor does

What it does

• Processes configured public sources or user-provided records for focused tender change v2 monitoring.
• Emits structured rows with source references, stable identifiers, confidence, warnings, and run summary fields.
• Supports sample-mode runs so Apify Store QA and first-time users can inspect output without depending on live third-party availability.

What it does not do

• Does not scrape private, login-only, paywalled, or access-restricted data unless the user provides approved credentials for a source they control.
• Does not guarantee every field is available from every source; missing or blocked fields are returned as warnings or nulls.
• Does not make legal, financial, compliance, procurement, medical, safety, or regulatory decisions.

Who this is for

Bid teams, procurement analysts, sales operations, consultants, and public-sector vendors use this actor when they need focused tender change v2 output instead of a broad generic scraper or manual checking.

Buyer outcomes

• Convert tender change v2 tender inputs into structured procurement intelligence.
• Prioritize review with extracted requirements, normalized language, classifications, changes, confidence, and source evidence.
• Route structured results into bid, sales, procurement, analyst, or compliance workflows.

Data sources

Sources monitored

official tender portals, procurement notices, buyer pages, public documents, and configured source URLs

Input

• sourceMode: use sample for a smoke run or configured tender page/PDF/source modes.
• startUrls: tender pages, PDFs, notices, buyer pages, or public procurement source URLs.
• sourceIds: approved tender, document, buyer, or procurement source identifiers.
• maxItems: bounded number of transformations, classifications, or changed tender records.
• watchlistTerms: buyer, CPV/category, requirement, region, language, or change terms.
• webhookUrl: optional destination for bid, procurement, or analyst review.
• outputMode: use sample records for Store validation or production output for normal runs.

How it transforms the input

• Input: tender page, PDF, buyer history, change record, CPV/category text, or multilingual tender text.
• Transformation: extract requirements, classify categories, normalize language, compare changes, or enrich buyer context.
• Output: structured tender intelligence with input reference, transformation type, extracted fields, confidence, and source evidence.

Output

The actor returns tender transformation records with input reference, extraction/classification/change output, source evidence, confidence, and review notes.

Family-specific fields to expect:

• inputReference: Tender page, PDF, buyer, or text input being transformed.

• transformationType: Classification, extraction, normalization, or change detection.

• extractedFields: Structured fields extracted from the input.

• confidence: Confidence for the transformation.

• sourceUrl: Source evidence URL.

• recordId: Stable record ID for exports, dedupe, and downstream joins.

• title: Human-readable record title for review and export.

• sourceName: Source identifier used to trace where the record came from.

• sourceUrl: Direct source URL for review and audit.

• dedupeKey: Stable key used for delta mode and duplicate suppression.

• retrievedAt: Timestamp showing when the actor retrieved or generated this record.

• score: Normalized field for filtering, routing, or downstream review.

• scoreReasons: Buyer-readable explanation for the score or match.

• confidence: Normalized field for filtering, routing, or downstream review.

• errors: Normalized field for filtering, routing, or downstream review.

• runSummary: Run-level summary for counts, filters, charges, and next actions.

Pricing

This actor uses Apify pay-per-event pricing. Current public listing guidance: $29-$49 / 1,000 launch validation records until public data proof is complete. Charges are tied to buyer-visible value events such as qualified-tender, dataset-processed, record-saved, enriched-record. Small validation runs are supported so you can inspect output before scaling a schedule.

• qualified-tender: Charge when Tender Change Monitor v2 produces Apify actor run or buyer-defined paid event. Typical price: $0.043. A run that produces 10 matching records charges only for the matched buyer-value events and remains capped by the run limit.
• dataset-processed: Base charge when Tender Change Monitor v2 writes a non-empty default dataset. Typical price: $0.011. A run that produces 10 matching records charges only for the matched buyer-value events and remains capped by the run limit.
• record-saved: Charge for each buyer-visible result saved by Tender Change Monitor v2. Typical price: $0.003. A run that produces 10 matching records charges only for the matched buyer-value events and remains capped by the run limit.
• enriched-record: Charge when Tender Change Monitor v2 adds match scoring, source evidence, or enrichment to a saved result. Typical price: $0.022. A run that produces 10 matching records charges only for the matched buyer-value events and remains capped by the run limit.
• first-run-cap: Recommended first run budget cap. Typical price: $3.820. Start with the default small run, inspect the dataset, then raise maxItems or schedule recurring runs.

API example

curl -X POST "https://api.apify.com/v2/actors/zentrafoundry~tender-change-monitor-v2/runs" \
+  -H "Authorization: Bearer $APIFY_TOKEN" \
+  -H "Content-Type: application/json" \
+  -d '{"maxItems":10,"sourceIds":[],"includeSourceUrls":true,"includeMatchReasons":true,"outputMode":"buyer-ready-records"}'

Demo run

Recommended first run

{
    "maxItems": 10,
    "sourceIds": [],
    "includeSourceUrls": true,
    "includeMatchReasons": true,
    "outputMode": "buyer-ready-records"
}

Sample output

Sample status: sample_unavailable at https://zentra.nimblique.studio/external/actor-review/samples/tender-change-monitor-v2.json. No fake sample is published; run a bounded real sample refresh before using examples in promotion.

Recommended public tasks

[
    {
        "name": "Transform 10 tender inputs",
        "description": "Low-cost validation run for checking extracted, normalized, classified, or changed tender fields.",
        "input": {
            "maxItems": 10,
            "sourceIds": [],
            "includeSourceUrls": true,
            "includeMatchReasons": true,
            "outputMode": "buyer-ready-records",
            "actorSlug": "tender-change-monitor-v2"
        }
    },
    {
        "name": "Daily tender intelligence review",
        "description": "Recurring batch for tender PDF, page, buyer, classification, or change intelligence.",
        "schedule": "Daily during local business hours",
        "input": {
            "maxItems": 25,
            "sourceIds": [],
            "includeSourceUrls": true,
            "includeMatchReasons": true,
            "outputMode": "buyer-ready-records",
            "actorSlug": "tender-change-monitor-v2"
        }
    }
]

Example use cases

• Extract or normalize tender change v2 tender inputs before manual procurement review.
• Turn PDFs, pages, buyer history, changes, or classifications into structured rows.
• Attach confidence, source references, and extracted fields for auditability.
• Route structured procurement intelligence to sales, bid, or analyst workflows.

Trust and compliance

• Uses official tender portals, procurement notices, buyer pages, public documents, and configured source URLs.
• Keeps source URLs and source identifiers in output records for auditability.
• Does not require private credentials unless a source is explicitly configured for approved authenticated access.

Reliability and QA

• Prefilled Apify Store QA input runs in sample mode and should finish within the automated quality window.
• Empty input is handled with deterministic sample or diagnostic output instead of a crash.
• Demo/sample runs suppress buyer-value charges while still writing representative dataset rows.
• Production runs use bounded maxItems, source references, warnings, and run summaries so blocked or changed targets are visible.

Limitations

• Results depend on public-source availability, source uptime, and source update cadence.
• Public sources can revise records after publication; rerun scheduled tasks for fresh evidence.
• Scores and match reasons are decision-support signals, not legal, financial, procurement, medical, safety, or regulatory advice.
• Large production runs can cost more than the default smoke run; start small, inspect output, then scale schedules.

Legal and responsible use

Use this Actor only for public data or data you are authorized to process. You are responsible for complying with applicable laws, marketplace terms, robots policies, privacy rules, and source-specific limits.

Support

Open an issue on the Actor page with the run ID, input summary, expected result, and observed result. Do not include secrets, cookies, auth headers, or private account data.

FAQ

Can I run this without URLs? Yes. The default sample mode is designed to succeed without user-supplied URLs, and URL-backed runs can use startUrls when needed.

Can I schedule it? Yes. Use sinceLastRun, watchlistTerms, and optional webhookUrl to turn the actor into a recurring alert or report workflow.

How do I verify value before scaling? Run the recommended first-run input, review the sample output fields, then increase maxItems or schedule recurring runs after the dataset matches your use case.