Finta Local Dev Loop
Overview
Finta is primarily UI-driven without a public API. For local automation, use CSV exports from Finta combined with Python scripts for analysis, reporting, and integration with other tools.
Instructions
Export Pipeline Data
- In Finta, go to Pipeline > Export > CSV
- Save as
pipeline-export.csv
Analyze Fundraise Pipeline
import pandas as pd
from datetime import datetime
df = pd.read_csv("pipeline-export.csv")
summary = df.groupby("Stage").agg(
count=("Name", "count"),
avg_check=("Check Size", "mean"),
).reset_index()
print("Pipeline Summary:")
print(summary.to_string(index=False))
stages = ["Researching", "Reaching Out", "Intro Meeting", "Follow-up", "Due Diligence", "Term Sheet", "Closed"]
for i in range(len(stages) - 1):
current = len(df[df["Stage"] == stages[i]])
next_stage = len(df[df["Stage"] == stages[i+1]])
rate = (next_stage / current * 100) if current > 0 else 0
print(f" {stages[i]} -> {stages[i+1]}: {rate:.0f}%")
Weekly Pipeline Report
def generate_weekly_report(df: pd.DataFrame) -> str:
total = len(df)
active = len(df[df["Stage"].isin(["Intro Meeting", "Follow-up", "Due Diligence"])])
term_sheets = len(df[df["Stage"] == "Term Sheet"])
closed = len(df[df["Stage"] == "Closed"])
return f"""
Fundraise Pipeline Report ({datetime.now().strftime('%Y-%m-%d')})
==================================================
Total investors: {total}
Active conversations: {active}
Term sheets: {term_sheets}
Closed: {closed}
"""
Resources
Next Steps
See finta-sdk-patterns for integration patterns.
