1from apify_client import ApifyClient
2
3
4
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7
8run_input = {
9 "mode": "analyze",
10 "deckInput": """Sample Startup Pitch:
11
12Problem: Small businesses struggle with customer support automation, spending $50K+ annually on support staff.
13
14Solution: Our AI-powered chatbot platform reduces support costs by 70% while improving response times.
15
16Market: $8.5B TAM in SMB customer support software, growing 18% YoY.
17
18Traction: 150 customers, $400K ARR, 25% MoM growth.
19
20Team: 2 founders with 15 years combined experience in AI and SaaS.
21
22Funding Ask: Raising $2M seed round for product development and sales team expansion.""",
23 "deckFile": "",
24 "batchMode": False,
25 "deckInputs": [],
26 "compareDecks": False,
27 "comparisonDeck2": "",
28 "comparisonDeck3": "",
29 "investorStage": "seed",
30 "investorFocus": "general",
31 "startupName": "Demo AI Startup",
32 "startupDescription": "An AI-powered customer support automation platform that helps small businesses reduce support costs by 70% while improving response times and customer satisfaction scores.",
33 "problemStatement": "",
34 "solutionStatement": "",
35 "targetMarket": "",
36 "businessModel": "",
37 "teamInfo": "",
38 "tractionInfo": "",
39 "competitorInfo": "",
40 "fundingAsk": "",
41 "industry": "saas",
42 "generateFromUrl": "",
43 "projectName": "",
44 "includeValuation": True,
45 "detectRedFlags": True,
46 "estimateDuration": True,
47 "generateCharts": True,
48 "generateRewrites": True,
49 "findInvestors": True,
50 "competitiveIntel": True,
51 "generateQA": True,
52 "executiveSummary": True,
53 "tailorForInvestor": "",
54 "aiProvider": "claude",
55 "apiKey": "",
56 "notifySlackWebhook": "",
57 "notifyDiscordWebhook": "",
58 "notifyEmail": "",
59}
60
61
62run = client.actor("actor_researcher.48/pitchdeck-analyzer-generator-pro-v-1").call(run_input=run_input)
63
64
65print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
66for item in client.dataset(run["defaultDatasetId"]).iterate_items():
67 print(item)
68
69
