Overview
News
Technologies
Salaries
Products
People
Growth
Offices
Jobs
Financials

Overview

Recover $15M+ in retail loss in year one. Used by 60+ of the Top 100 U.S. retailers across 40% of all U.S. transactions, with 99.99% decision accuracy.

News

Blog 22 days ago
Collapse a coordinated return fraud ring without a policy change
Closing a $1M return fraud scheme required a four-step process, a technical partner, and one 15-minute fix. It's the same people all day, every day. That's what an investigative systems expert says about a coordinated group that had cracked a gap in a maj
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Blog 2 months ago
What enterprise retailers get wrong when they evaluate AI
Why the vendor demoing the flashiest agent rarely moves your return rate A doctor who correctly reads the scan but labels the condition wrong doesn't help the patient. The treatment that follows is built on a real result and the wrong conclusion. This pla
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Blog 2 months ago
When retail loss prevention stops chasing ghosts and starts protecting margins
How retail executives can transform loss prevention from cost center to competitive advantage Most retail organizations treat returns, fraud, abuse, and shrink like distant relatives who only see each other at awkward family gatherings. Loss prevention ha
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Blog 3 months ago
Why high-volume fraud alerts are wasting your investigators' time
Triple investigator productivity by changing what criteria your alerts are based on. Welcome to the forest of fraud (stay with us). Imagine every tree that sprouts is a specific case of fraud and abuse. By the time a tree is mature, the roots have been th
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Blog 4 months ago
Who owns agentic commerce fraud when it lands on your P&L?
Retailers have spent years building the exact return policies that agentic commerce is using against them Enterprise retailers have spent years building attribution infrastructure for the front door. UTM parameters log every click Attribution models tell
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Blog 4 months ago
The AP Leader Who Has to Win Two Rooms
Loss, leadership buy-in, and the business case that keeps failing Drones look cooler in PowerPoint slides than database fixes. An investigative systems expert learned this managing systems across all of their company's brands. The theft where local law en
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Blog 5 months ago
How a 3-layer AI architecture applies to returns management
What LP, ops, and ecom teams miss when they only see dashboards and alerts Welcome to the penthouse, where LP, ops, and ecom teams are querying data, reviewing dashboards, and acting on partial returns data or alerts someone else surfaced. What they seldo
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Blog 6 months ago
What a Pair of Shorts Can Teach You About Return Root Causes
How to Calculate the True Cost of Returns and Use Data to Reduce Them Retailers care a lot about returns. They hurt their business, so it's natural that they look for ways to stop the bleeding. Can we process these faster? Consolidate them cheaply? Route
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Blog 6 months ago
Breaking the "Receipts Equal Safe" Assumption: Executive Education for Fraud Prevention
Software can flag fraud, but only people can change how departments work. A veteran asset protection manager at a large retailer spent years managing returns fraud and financial fraud initiatives across 2,000+ stores. During that time, they discovered tha
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Tech stack

Technologies named in job postings at Appriss Retail over the last 12 months, by layer, with the share of postings for each.
Technologies in use
23
Postings analysed
3
Stack modernity
85/100AI adopter
Languages
Python
SQL
Frameworks & libraries
LangChain
LlamaIndex
Databases
Snowflake
Cloud & platforms
AWS
Azure
GCP
MLFlow
AI & ML
Claude
LLM
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Full Appriss Retail tech stack 23 technologies · by team · pay by technology · changes · similar stacks

People

Heather Magaro
Executive Officer
Michael Osborne
Executive Officer
Krishnan Sastry
Director
Michael Davis
Director
Scott Barclay
Director
Behdad Eghbali
Director
Anika Agarwal
Director
Paul Huber
Director
Names and roles come from public filings, company registers and the company's own site. Is this you? Correct or remove · How we handle this data

Growth

Hiring Momentum
43/100
Stable
Open positions
4
0 opened / 4 closed in 30 days
Median time-to-fill
69 days
faster than 20% of the market
ATS activity
Every ~3 hours
Today
Hiring Dynamics +100%
Hiring Focus
The percentage next to each role is its share of the company's job openings over the last 90 days; the arrow shows the shift versus the previous period.
Data Science
33% ▲
Product
33% ▼
Customer Success
33% ▼

Offices

Where the company hires and what each office is for
Cities
1
Hiring now
0
Countries
1
Irvine United States
HQ
50-200 est. staff

Jobs

≈ $137k – $231k per year (Estimated) • Remote (United States) • Full-Time • 6+ years exp • Bachelor's Degree
Python
SQL
Snowflake
AI/ML
LangChain
Spark
LlamaIndex
MLFlow
dbt
Fine-tuning
Prompt Engineering
Function Calling
AI Agents
LLM
RAG
Feature Store
Agentic Workflows
Tool Use
DevOps
Terraform
GCP
CloudFormation
Azure
CI/CD
AWS
Docker
Kubernetes
Apply
≈ $92k – $172k per year (Estimated) • Remote (United States) • Full-Time • 3+ years exp
Jira
Agile
Scrum
Apply
≈ $124k – $213k per year (Estimated) • Remote (United States) • Full-Time • 6+ years exp • Bachelor's Degree
Python
SQL
Snowflake
AI/ML
LangChain
Spark
LlamaIndex
MLFlow
dbt
Fine-tuning
Prompt Engineering
Function Calling
AI Agents
LLM
RAG
Feature Store
Agentic Workflows
Tool Use
DevOps
Terraform
GCP
CloudFormation
Azure
CI/CD
AWS
Docker
Kubernetes
Apply

Financials

Total raised
$13.8M
Latest round
Venture - Series Unknown
Funding rounds
1
Funding rounds
Round Announced Amount
Venture - Series Unknown 2023 $13.8M Details