Flim
Flim·Creative Technology·Startup

How Flim automated inbound qualification reducing ~90% of manual work

Flim is the all-in-one platform for visual storytelling, powering creative work across Hollywood, music, fashion, gaming, and beyond. Their account managers were spending 6 hours a week manually researching and classifying inbound leads. With Fluar, every signup is now automatically enriched, scored, and routed, cutting qualification time by ~90%.

Maria Paula Pinzon

Kamil Kyzo

Co-founder, Fluar

~90%Less manual work
100%Inbound auto-enriched
3-tierICP scoring
2×/weekEnrichment runs
We tried ChatGPT, Perplexity, and Claude. It was messy. One was good at company names but bad at classification. Fluar just worked. The prompting was fluid.
Maria Paula Pinzon

Maria Paula Pinzon

Account Manager, Flim

Inbound Lead Enrichment Pipeline

From raw signup to classified, language-routed lead

1
Fluar
New signups imported
Source

Flim.ai back office export

2
OpenAI
Resolve company name
Found

Wieden+Kennedy

3
OpenAI
Identify HQ country
Location

United States

4
LinkedIn
Pull LinkedIn employees
Size

1,200 employees

5
OpenAI
AI tier classification
Tier 1

Major ad agency

6
Mixmax
Export to Mixmax
Sent

EN sequence, 3 emails

01

The Challenge

Flim generates hundreds of signups weekly. But turning those signups into revenue required manual research: resolving company names from domains, identifying headquarters countries for multilingual outreach, and pulling LinkedIn employee counts to classify and prioritize leads.

The process took 3 hours per batch, twice a week. General-purpose AI tools couldn't handle the volume or maintain consistent classification across hundreds of rows.

02

Why Fluar

Maria had tried Hunter.io and PhantomBuster, but found them too limited or too technical. She needed something she could set up herself. No developers, no code.

Fluar's spreadsheet interface matched how she already thought about the problem. She described her classification criteria in plain language, chained multiple enrichment steps in sequence, and ran the entire pipeline from a single table. What used to require 3-4 different tools happened in one place.

Integrations used

03

The Solution

Maria built a 6-step enrichment pipeline that mirrors her manual process: import signups → resolve company name → identify HQ country → pull LinkedIn employee count → AI tier classification → export to Mixmax.

The AI classification column uses her exact criteria to categorize every lead consistently. Each tier feeds into a different email sequence, sent in the prospect's language (English, French, or Spanish) based on the headquarters country Fluar identified.

04

The Results

What used to take 6 hours per week now takes 30 minutes. Maria spends the reclaimed time on actual selling instead of data entry.

The impact goes beyond time savings. Consistent, automated tier classification means the right agencies get the right offers faster. Outreach is more targeted, conversion rates are higher, and each converted customer has stronger long-term retention.

A single conversion is enough to justify the cost of Fluar. But with automated enrichment running twice a week across every new signup, Flim converts multiple accounts per month.

Fluar was a huge game changer. I used to do this manually for 6 hours. Now it takes 30 minutes. For my process, it's perfect and super simple.
Maria Paula Pinzon

Maria Paula Pinzon

Account Manager, Flim

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