Every organization has manual processes that burn hours, waste money, create bottlenecks, and introduce errors. We replace them with AI systems that learn over time, run in production, and save thousands of hours and millions of dollars at scale.
Before
Analyst teams manually reviewed ~28K trades per week hunting for compliance risks. Rules-based alerts generated high volumes of low-priority noise.
FIS · Financial Services
→
After
AI automatically classifies 100% of compliance risks. Multivariable risk scoring isolates legitimate threats. Analysts focus on what matters.
~98.5% reduction in manual review
Before
Marketers manually wrote copy and product descriptions across seasons, personas, and thousands of SKUs — one at a time.
Under Armour · Retail
→
After
An AI generation pipeline creates editable product detail page content and optimized copy on demand, at scale.
86% faster · 6 weeks → 6 days
Before
Locking in forecast edits and carrying over promotional elements drove delays of over 48 hours per planning cycle.
Conagra Brands · CPG
→
After
Automated pipelines with dynamic tables and Snowpark eliminate manual carryover. Forecasts process every cycle without delay.
26% faster forecast processing
Systems
Data in. Decisions out. Automated.
Every automation follows a specific architecture. Data flows in, AI processes it in real time, and the right output reaches the right person, agent, or system. Each implementation is tailored to the client's data and workflow.
Example Automation Architectures →
Not Theoretical
Production-Grade Systems at Work
These are not experiments or proofs of concept. Every system runs in production, processes real data at scale, and delivers measurable outcomes.
Not a Black Box
Your Data, Your Environment
Everything runs inside your Snowflake environment. Your data never leaves. Full governance, audit trails, and role-based access from day one.
Not One-Size-Fits-All
Tailored to Your Workflow
We don't deploy a generic tool. Every automation is designed around your specific data sources, business rules, and operational needs.
Not Static
Learns and Improves
Human feedback refines the system over time. It gets smarter the longer it runs, adapting to new patterns and edge cases.
"We felt like we were driving a Volkswagen before, now it feels like we're driving a Rolls Royce."
FIS client · Hakkoda's Snowflake Cortex alert classification system
Success
Real Results Across Industries.
Not presentations. Not projections. These are production systems operating live for global enterprises at scale.
98.5%
Reduction in manual review volume
FIS
86%
Reduction in campaign creation time
Under Armour
26%
Faster demand forecast processing
Conagra Brands
Client results
More results, more industries.
Production-grade automation deployed across financial services, retail, CPG, healthcare, automotive, and supply chain.
Client
Automation type
Result
FIS
Financial Services
AI trade alert classification using Snowflake Cortex and LLM-based risk scoring. Replaced a rules-based system generating high volumes of redundant alerts.
~98.5%reduction in manual review volume
Under Armour
Retail
AI content generation pipeline for product descriptions and campaign copy. Replaced manual, one-at-a-time copywriting across thousands of SKUs.
86% faster6 weeks → 6 days per campaign cycle
Conagra Brands
CPG · $12B revenue
Automated forecast carryover pipelines using dynamic tables and Snowpark. Eliminated 48-hour planning delays caused by manual data movement between cycles.
26% fasterdemand forecast processing, every cycle
Caliber Collision
Automotive Services
AI copilot-accelerated BI rationalization and Snowflake migration. Over 2,000 reports automated and transformed. Legacy SQL Server retired.
70% fastertime to value · 6 weeks vs. 8-month SI estimate
Century Distribution
Supply Chain / Logistics
Automated data pipelines eliminating manual errors across 511 SQL tables and 231 SSIS packages. Migrated to Snowflake with Azure Data Factory.
10xreduction in DBA ops time · $121K annual savings
Capital Group
$2.6T AUM · Financial Services
Automated web scraping and LLM-based sentiment analysis for quant trading strategy. Executive summaries generated on demand from hundreds of news sources.
Structural proof
Manual research eliminated. Quant decisions data-driven in real time.
Medtronic
$33.5B revenue · Healthcare
AI supplier intelligence app on Cortex Analyst. Three semantic models connected. Conversational interface surfaces procurement KPIs instantly.
Structural proof
Manual procurement research eliminated. Enterprise expansion greenlit post 8-week build.
