Enrich Contacts with Company Data

Merging contact records with fund data breaks when "Bridgewater" needs to match "Bridgewater Associates" and "D.E. Shaw" needs to match "D. E. Shaw & Co." This case study demonstrates fuzzy matching that understands company name conventions.

Metric	Value
Rows processed	10
Matched	10 (100%)
Total cost	$0.00
Time	9 seconds

Add FutureSearch to Claude Code if you haven't already:

claude mcp add futuresearch --scope project --transport http https://mcp.futuresearch.ai/mcp

With both CSVs in your working directory, tell Claude:

Merge crm_contacts.csv with crm_funds.csv. Match contacts to their fund based
on company name, ignoring legal suffixes (LLC, Inc, LP), abbreviations
(Mgmt = Management, Tech = Technologies), and extra descriptors.

Claude calls FutureSearch's merge MCP tool:

Tool: futuresearch_merge
├─ task: "Match contacts to their associated fund/company..."
├─ left_csv: "/Users/you/crm_contacts.csv"
├─ right_csv: "/Users/you/crm_funds.csv"
├─ merge_on_left: "company_name"
├─ merge_on_right: "fund_name"
└─ relationship_type: "one_to_one"

→ Submitted: 10 rows for merging.
  Session: https://futuresearch.ai/sessions/8e2eb233-e2cb-4144-b949-0e4fb4962cb2

Tool: futuresearch_results
→ Saved 10 rows to /Users/you/merged_contacts.csv

All 10 matched in 9 seconds for $0.00. View the session.

Add the FutureSearch connector if you haven't already. Then upload crm_contacts.csv and crm_funds.csv and ask Claude:

Merge crm_contacts.csv with crm_funds.csv. Match contacts to their fund based on company name, ignoring legal suffixes (LLC, Inc, LP), abbreviations (Mgmt = Management, Tech = Technologies), and extra descriptors.

Go to futuresearch.ai/app, upload crm_contacts.csv and crm_funds.csv, and enter:

Merge crm_contacts.csv with crm_funds.csv. Match contacts to their fund based on company name, ignoring legal suffixes (LLC, Inc, LP), abbreviations (Mgmt = Management, Tech = Technologies), and extra descriptors.

pip install futuresearch
export FUTURESEARCH_API_KEY=your_key_here  # Get one at futuresearch.ai/app/api-key

import asyncio
import pandas as pd
from futuresearch import create_session
from futuresearch.ops import merge

contacts_df = pd.read_csv("crm_contacts.csv")
funds_df = pd.read_csv("crm_funds.csv")

async def main():
    async with create_session(name="CRM Merge Workflow") as session:
        result = await merge(
            session=session,
            task="""
                Match contacts to their associated fund/company.
                Company names may vary between tables. Match on core company name,
                ignoring legal suffixes, abbreviations, and descriptors.
            """,
            left_table=contacts_df,
            right_table=funds_df,
            merge_on_left="company_name",
            merge_on_right="fund_name",
        )
        return result.data

merged = asyncio.run(main())

Results

Contact	Company (left)	Fund (right)
John Smith	Bridgewater	Bridgewater Associates
Sarah Johnson	Citadel LLC	Citadel
Jessica Wang	D.E. Shaw	D. E. Shaw & Co.
Robert Brown	Point72 Asset Mgmt	Point72 Asset Management
Amanda Wilson	Renaissance Tech	Renaissance Technologies

The merge cascade handled all variations (abbreviations, suffixes, spacing) via fuzzy matching without needing LLM calls. When simpler methods work, FutureSearch uses them.

Enrich Contacts with Company Data

Metric	Value
Rows processed	10
Matched	10 (100%)
Total cost	$0.00
Time	9 seconds

Add FutureSearch to Claude Code if you haven't already:

claude mcp add futuresearch --scope project --transport http https://mcp.futuresearch.ai/mcp

With both CSVs in your working directory, tell Claude:

Merge crm_contacts.csv with crm_funds.csv. Match contacts to their fund based
on company name, ignoring legal suffixes (LLC, Inc, LP), abbreviations
(Mgmt = Management, Tech = Technologies), and extra descriptors.

Claude calls FutureSearch's merge MCP tool:

Tool: futuresearch_merge
├─ task: "Match contacts to their associated fund/company..."
├─ left_csv: "/Users/you/crm_contacts.csv"
├─ right_csv: "/Users/you/crm_funds.csv"
├─ merge_on_left: "company_name"
├─ merge_on_right: "fund_name"
└─ relationship_type: "one_to_one"

→ Submitted: 10 rows for merging.
  Session: https://futuresearch.ai/sessions/8e2eb233-e2cb-4144-b949-0e4fb4962cb2

Tool: futuresearch_results
→ Saved 10 rows to /Users/you/merged_contacts.csv

All 10 matched in 9 seconds for $0.00. View the session.

Add the FutureSearch connector if you haven't already. Then upload crm_contacts.csv and crm_funds.csv and ask Claude:

Merge crm_contacts.csv with crm_funds.csv. Match contacts to their fund based on company name, ignoring legal suffixes (LLC, Inc, LP), abbreviations (Mgmt = Management, Tech = Technologies), and extra descriptors.

Go to futuresearch.ai/app, upload crm_contacts.csv and crm_funds.csv, and enter:

Merge crm_contacts.csv with crm_funds.csv. Match contacts to their fund based on company name, ignoring legal suffixes (LLC, Inc, LP), abbreviations (Mgmt = Management, Tech = Technologies), and extra descriptors.

pip install futuresearch
export FUTURESEARCH_API_KEY=your_key_here  # Get one at futuresearch.ai/app/api-key

import asyncio
import pandas as pd
from futuresearch import create_session
from futuresearch.ops import merge

contacts_df = pd.read_csv("crm_contacts.csv")
funds_df = pd.read_csv("crm_funds.csv")

async def main():
    async with create_session(name="CRM Merge Workflow") as session:
        result = await merge(
            session=session,
            task="""
                Match contacts to their associated fund/company.
                Company names may vary between tables. Match on core company name,
                ignoring legal suffixes, abbreviations, and descriptors.
            """,
            left_table=contacts_df,
            right_table=funds_df,
            merge_on_left="company_name",
            merge_on_right="fund_name",
        )
        return result.data

merged = asyncio.run(main())

Results

Contact	Company (left)	Fund (right)
John Smith	Bridgewater	Bridgewater Associates
Sarah Johnson	Citadel LLC	Citadel
Jessica Wang	D.E. Shaw	D. E. Shaw & Co.
Robert Brown	Point72 Asset Mgmt	Point72 Asset Management
Amanda Wilson	Renaissance Tech	Renaissance Technologies

The merge cascade handled all variations (abbreviations, suffixes, spacing) via fuzzy matching without needing LLM calls. When simpler methods work, FutureSearch uses them.