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Discover how the TazWorks–Cerebrum Synapse integration empowers CRAs with more consistent outcomes, fewer exceptions, and stronger growth.
AI has officially moved from “interesting experiment” to “strategic priority,” and background screening is no exception. In a recent webinar, TazWorks Director of Product Management Jake Shapiro and Cerebrum Founder & CEO Sebastian Mellen walked attendees through what AI can actually do for CRAs today, what risks need to be managed, and how the new TazWorks–Cerebrum Synapse integration is designed to deliver real efficiency without sacrificing consistency, compliance, or control.
If you’ve been hearing more AI questions in RFPs or are simply looking for a way to reduce repetitive manual processing while improving standardization, this session was built for you.
Below is a recap of the key takeaways and a look at what Synapse enables inside the TazWorks ecosystem.
AI in Screening: The Train Has Left the Station
Early in the webinar, attendees were polled on how leadership views AI in screening. The results were telling: most respondents saw AI as an opportunity or believed it could be useful, while a meaningful portion still held “time will tell” skepticism. Notably, no one chose “AI is not for us.”
That lines up with what many teams are experiencing right now:
- AI questions are appearing more frequently in RFPs
- End customers are asking how CRAs are using AI (and whether they should be concerned)
- Internal teams are experimenting with AI tools, even when leadership isn’t formally “all in” yet
As Jake put it, the technology shift is already underway, and the industry’s challenge now is learning how to harness it responsibly.
The Real Risk: “Generative” Isn’t the Same as “Deterministic”
One of the strongest threads of the webinar was a clear distinction between AI that produces variable outputs and AI designed for repeatable, auditable workflows.
Sebastian shared a cautionary example where attorneys used generative AI to draft legal briefs, and the AI “hallucinated” cases that didn’t exist, leading to sanctions and serious consequences.
It’s an extreme illustration, but the core point lands: in regulated environments, unpredictability is a liability.
Subsequently, the conversation repeatedly returned to a non-negotiable requirement for screening: decisions must be consistent, traceable, and explainable. The same inputs should not generate a different recommendation tomorrow than they do today. If a workflow can’t be audited, it doesn’t belong in the process, no matter how exciting the tech looks in a demo.
This is the logic behind why Synapse is positioned as AI operational tooling that supports repeatable screening rules with clear decision trails rather than a simple “chatbot for screening.”
Where AI Creates Value for CRAs: Three Practical Pillars
The discussion broke down the value of AI in screening into three distinct, CRA-focused buckets.
- Growth
AI is increasingly part of buyer expectations. Even when deals aren’t lost directly because of AI today, many CRAs anticipate it becoming a factor soon. That’s consistent with the results from the second webinar poll: most respondents haven’t seen AI-driven deal losses yet, but feel the pressure building.
But while defense is important, offense is the bigger opportunity.
Sebastian emphasized that screening still has major opportunities for expansion, highlighting industries and use cases where background checks aren’t consistently done today because the process can feel too slow or too operationally heavy. Faster, more scalable workflows can unlock new volumes and new markets, especially for organizations that need speed and consistency.
2. Operations
Synapse is designed to automate the repetitive “first-in-file” work—pattern matching, standard filtering, basic triage—so humans can focus on what they’re uniquely good at:
- Complex, nuanced cases
- Customer communication and service recovery
- Differentiated searches
- Exceptions and edge-case decisioning
This enables experienced teams to focus on high-value tasks while reducing the grind that drives turnover and makes scaling painful (especially during seasonal spikes).
3. Risk & Compliance
Jake pointed out that two processors can read the same process document and still interpret it differently in practice. That inconsistency creates operational and reputational downstream risk.
Synapse is built to help CRAs standardize and operationalize judgment logic. And because the system produces audit trails and workflow paths, teams can understand why a decision was made—something that’s notoriously difficult to reconstruct with human memory alone.
How Synapse “Thinks” About Language
Before the demo, Sebastian walked through a foundational concept called embeddings, which are a way of representing the meaning of words mathematically so a system can determine which concepts are related.
Screening data often includes messy, inconsistent offense descriptions that humans can look at and quickly decide, “That’s minor noise,” or “That deserves attention.” Synapse uses embedding-driven models trained on large datasets to do something similar at scale, without improvising or “making up” new information.
The important nuance to note is that Synapse is sorting and classifying returned data into a decision framework your team controls.
The Synapse Workflow Builder: Turning Policy into Repeatable Logic
At the heart of Synapse is a workflow builder that enables CRAs to encode decision logic transparently.
In the webinar example, Sebastian described a simplified workflow, such as:
- Identify whether an offense is traffic-related
- Only retain traffic offenses if they are felonies
- Apply age-based rules (for example, older than seven years)
- Route “unsure” scenarios to manual review
- Surface “keep” items for QA rather than pushing anything directly to an end user
Synapse is designed to be deterministic, meaning the same inputs follow the same logic path every time. That predictability is what makes it usable in screening operations.
What Synapse Does in Practice: Case Formation + Automated Record Review
Synapse is structured around two major stages that map to real CRA workflows:
- Case Formation
This is where Synapse evaluates the initial identity and trace inputs (such as alias history and address history) and helps determine:
- Which jurisdictions should be searched
- Which names should be searched (based on your scoping rules)
- What to exclude (such as misspellings, unwanted alias types, or names outside a time window)
Sebastian gave examples of how customizable this can be, including whether to include nicknames, how far back to look, and how to handle scenarios like maiden names or ambiguous name patterns.
- Automated Review of “Pointer File” Results
Next, Synapse helps process returned records from searches like NatCrim (and soon, eviction). The webinar highlighted two key capabilities:
- Suppression: filter out records CRAs often don’t care about (like minor traffic/equipment violations)
- More advanced filtering: apply CRA-specific interpretations of FCRA/state rules and record attributes, with support for actions like ordering confirmations based on logic
The goal is to reduce the volume of “noise” your team must manually review, while ensuring anything uncertain is appropriately routed for human attention.
Demo Spotlight: NatCrim Processing Inside TazWorks
In the live demo, a sample report (“Hank Mess”) showed multiple returned records. The TazWorks-Cerebrum Synapse integration processed the file and:
- Retained potentially reportable records based on rules (e.g., within seven years, reportable classification, pending vs non-conviction outcomes)
- Withheld records that met configured suppression/filters (for example, non-convictions in a jurisdiction where the CRA policy would not keep them)
- Provided a linkable workflow trail showing exactly which decision nodes were traversed and why
Jake underscored an important product philosophy here: the front-end experience should stay simple. The intelligence runs in the background, but processors and QA teams still see what they need, such as recommendations, notes, and the option to audit the “why” behind outcomes.
Automation That Supports Your Decisions, Not Replaces Them
The webinar’s strongest throughline was that Synapse is built to help CRAs scale and standardize work without turning screening into a black box.
It’s about practical automation that:
- Reduces repetitive processing
- Improves consistency across teams
- Provides auditability and traceable decision paths
- Keeps humans in control of what gets finalized and delivered
And because it’s integrated into TazWorks, it’s designed to fit within CRAs’ existing workflows without introducing unnecessary complexity for processors and QA.
See the TazWorks–Cerebrum Synapse Integration in Action
If you’re exploring how to speed up turnaround times, reduce noise in first-in-file workflows, and strengthen consistency with deterministic AI, this integration is worth a closer look.