How Pensa Systems Built a Scalable Outbound Engine for Enterprise CPG with Bitscale

About Pensa Systems

Pensa Systems is the leader in Vision AI for retail — helping CPG brands and retailers eliminate stockouts, enforce shelf compliance, and maximize on-shelf availability across tens of thousands of stores globally. Founded in 2016 and backed by $17.2M in funding, Pensa has deployed its AI-powered shelf monitoring technology with some of the world's largest consumer brands, including Johnson & Johnson, General Mills, Anheuser-Busch InBev, and Unilever.

The company's platform uses computer vision and motion-based AI to scan retail shelves in seconds, automatically identifying what's on shelf, what's missing, and what needs attention — giving CPG and retail teams real-time visibility that was previously impossible at scale. Pensa now operates across 70+ retailers on four continents, spanning 150+ product categories.

With a growing enterprise sales motion, Pensa's business development team needed to match the precision of their product with the precision of their outbound.

The Challenge

Selling Vision AI to enterprise CPG companies is not a spray-and-pray motion. The buyers are specific — category managers, VP of Retail Operations, Supply Chain Directors — at companies that operate at massive scale and expect vendors to understand their world before the first conversation.

For Pensa's business development team, that meant their outbound process had to be both highly targeted and highly personalized. But their existing toolchain couldn't deliver either at scale. Building accurate prospect lists was manual and time-consuming. Getting reliable email addresses and phone numbers for senior decision-makers at enterprise CPG companies was inconsistent — single-provider tools regularly came up empty. And personalizing outreach to each prospect's specific context required effort that didn't scale beyond a handful of contacts per day.

The result was an outbound motion that relied heavily on manual effort, underperformed on contact coverage, and couldn't keep pace with the pipeline targets the team needed to hit.

The Solution

Pensa onboarded Bitscale and built a four-part outbound engine that handles everything from list construction to personalized send-ready messaging — without manual intervention at any step.

1. Targeted List Building

The team starts by using Bitscale's list building capabilities to identify the right personas at the right companies. Rather than pulling broad exports from a single database, Pensa builds precise lists filtered by industry, company size, job function, and seniority — ensuring every contact in the workflow matches their ICP before enrichment even begins. With access to Bitscale's database of 40M+ companies and 300M+ people, the team can surface net-new prospects they would never have found through manual research.

2. Email Waterfall Enrichment

Finding valid email addresses for senior enterprise decision-makers is notoriously difficult. Single-provider tools frequently return empty results or outdated data. Pensa solves this with Bitscale's waterfall email enrichment — a sequential check across 14+ data providers that automatically tries the next provider if the previous one fails. The result is dramatically higher coverage than any single-source approach, with verified emails for contacts that would otherwise fall through the cracks.

3. Phone Number Waterfall

For accounts where multi-channel outreach makes sense, Pensa runs a parallel waterfall for phone number enrichment — giving the team the ability to reach decision-makers by phone without a separate process or additional tooling. The same waterfall logic applies: cycle through providers, verify results, and surface the best available data.

4. Personalized Outbound Content at Scale

The final step is where Bitscale's AI layer turns enriched data into ready-to-send outreach. Pensa uses Bitscale's content personalization workflows to generate outbound messages tailored to each prospect — referencing their category, retailer relationships, or shelf-specific challenges. What used to require an SDR to write each message individually now happens automatically at the scale of thousands of contacts, without sacrificing the relevance that makes enterprise outreach land.

The Results

Pensa's outbound engine now processes over 29,000 rows through Bitscale workflows every month — a volume of prospecting activity that would have been impossible with their previous manual setup.

Metric Before Bitscale After Bitscale List building process Manual, time-intensive Automated, filter-driven Email coverage for enterprise ICPs Inconsistent (single provider) High coverage (14+ provider waterfall) Phone number enrichment Separate manual process Automated waterfall, same workflow Outreach personalization Manual, limited to small batches AI-generated at scale, per contact Monthly workflow volume Constrained by manual capacity 29,000+ rows/month

The shift from manual to automated has compounded across every stage of the outbound process. The business development team now spends less time sourcing and enriching data and more time having the conversations that close deals.

What's Next

With their core outbound engine running at scale, Pensa is expanding what they build on Bitscale. Upcoming workflows include account-level research automation — using Bitscale's AI research layer to surface relevant signals about each prospect's retail footprint, recent product launches, and category performance — allowing the team to go into every conversation with insights that make the opening line impossible to ignore.

For a company whose product is built on the idea that better data leads to better outcomes, Bitscale's role in Pensa's GTM is a natural extension of the same philosophy — applied to the outbound motion itself.