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How it Works
Our agents optimize how your data warehouse scales, schedules, and runs queries.
Scheduling Agent
autoscale warehouses, reroute workloads
Query Agent
Scheduling Agent
Run your data warehouse like Google runs its datacenters.
Smarter scaling
Snowflake's multicluster scaling uses the same algorithm for every workload, leaving a ton of credits on the table.
Our agents analyze and scale each workload independently, leading to utilization gains of 25%+.
Realtime Scheduling
Instead of routing each query to a fixed warehouse, our agent analyzes your running workloads to understand where to send the query to maximize utilization without impacting performance, increasing savings to 40%+.
Stop paying for idle warehouses
The average Snowflake user's warehouse utilization is between 40% and 60%. That means half your compute spend is on idle machines.
Our real-time, neural scheduler brings idle time below 10%.
select NATION.N_NAME as N_NAME, COUNT(1) as "cnt:C_NAME:ok"
from SNOWFLAKE_SAMPLE_DATA.TPCH_SF1000.CUSTOMER CUSTOMER
inner join SNOWFLAKE_SAMPLE_DATA.TPCH_SF1000.NATION NATION
on (CUSTOMER.C_NATIONKEY = NATION.N_NATIONKEY)
where CUSTOMER.C_MKTSEGMENT not
in ('AUTOMOBILE') and CUSTOMER.C_MKTSEGMENT is not null
group by NATION.N_NAME; select t0.N_NAME as N_NAME, SUM(1) as "cnt:C_NAME:ok"
from SNOWFLAKE_SAMPLE_DATA.TPCH_SF1000.CUSTOMER CUSTOMER
inner join (
select CUSTOMER.C_NATIONKEY as C_NATIONKEY, NATION.N_NAME as N_NAME
from SNOWFLAKE_SAMPLE_DATA.TPCH_SF1000.CUSTOMER CUSTOMER
left join SNOWFLAKE_SAMPLE_DATA.TPCH_SF1000.NATION NATION
on (CUSTOMER.C_NATIONKEY = NATION.N_NATIONKEY)
group by 1,2) t0
on (CUSTOMER.C_NATIONKEY = t0.C_NATIONKEY)
where (case when ((CUSTOMER.C_MKTSEGMENT in ('AUTOMOBILE'))
or (CUSTOMER.C_MKTSEGMENT IS NULL)) then FALSE else TRUE end)
group by 1;Query Agent
Our query agent optimizes your SQL on the wire.
Neural Optimization
We use LLMs for optimization, automating query improvements that previously required human experts.
It's like having an expert data engineer look at every piece of SQL before it hits your data warehouse.
Formal Verification
Our agents don't hallucinate. Every optimization is cross-checked using formal verification, ensuring that the optimized query is mathematically equivalent to the original.
Optimize Everything
Your handwritten SQL might be good - but what about ORM-generated queries, or one-off analyst queries typed straight into Snowflake's UI?
Our agent works with every query, no matter where it comes from, leading to improved performance and reduced costs across the board.