Stocha

Technology and financial services simulation

Queues for compute, analysts and settlement, batches that close on a clock and rework loops in review. Pick the decision, such as how many accelerators or analysts a peak needs, and test it before demand arrives.

Each is a scenario Stocha is built to model.

AI inference capacity

Decision: how many accelerators keep chat waits acceptable at your busiest hour, and does reserving part of the pool for chat beat adding capacity? The model sends chat requests and multi-step agent jobs through one accelerator pool and a human review desk. You read the average chat wait with its confidence interval for each plan.

What flows
Chat request, agent job, reviewed agent output
What is scarce
Accelerator, reserved chat accelerator, human reviewer
Where it waits
Accelerator queue, agent step queue, review desk queue

Questions you can test

  • How many accelerators keep the wait for a chat answer acceptable at the busiest hour?
  • Does reserving part of the pool for chat help more than adding capacity?
  • How many users leave before their answer starts when the queue grows?
  • When can agent jobs run without hurting live chat?
  • How much review capacity do agent jobs need before they pile up?

Edge and industrial cloud capacity

Decision: how many edge nodes and which group size stop sensor data from waiting for the uplink window? The model sends sensor bursts through edge compute slots and holds the rest until the uplink opens. You read the longest data wait with its confidence interval for each plan.

What flows
Sensor reading, reading group, cloud job
What is scarce
Edge compute slot, uplink window, cloud worker
Where it waits
Edge input buffer, uplink waiting area, cloud job queue

Questions you can test

  • How many edge nodes handle a shift-start burst without a growing backlog?
  • What group size balances edge load against cloud cost?
  • How long must the uplink stay open to clear the backlog?
  • What happens to latency when one edge node fails?
  • Does moving a processing step from the cloud to the edge shorten the path?

Semiconductor fab cycle time

Decision: which dispatch rule or tool count shortens wafer-lot cycle time? The model sends each lot through the same tool group on every layer, with tool failures and the lots queued in front of the slowest step. You read cycle time and work in progress with confidence intervals.

What flows
Standard lot, hot lot, test lot
What is scarce
Lithography stepper, etch tool, deposition tool, maintenance technician
Where it waits
Lithography queue, etch queue, deposition queue, batch wait before furnace

Questions you can test

  • Which tool group limits cycle time at the current release rate?
  • How much does one more stepper cut the wait compared with a faster repair?
  • What does hot lot priority cost the standard lots?
  • How many lots can be released per week before work in progress climbs sharply?
  • Does batching lots for the furnace save more than it delays?

Security operations alert triage

Decision: how many analysts per shift and which escalation rule hold response time when an alert burst hits? The model sends alerts through first review, escalation to senior staff and expiry of low-priority alerts. You read response time with its confidence interval at the burst.

What flows
High-priority alert, low-priority alert, escalated case, identity verification check
What is scarce
First-line analyst, senior analyst, on-call responder
Where it waits
First-line alert queue, escalation queue, verification check queue

Questions you can test

  • How many first-line analysts does the night shift need to clear a burst?
  • What share of low-priority alerts goes unread, and does a rule change fix it?
  • How long do escalated cases wait for a senior analyst?
  • Does a dedicated senior analyst for escalations beat a shared pool?
  • How much does a noisy detection rule cost in analyst hours?

Payment processing throughput

Decision: does your screening, matching and settlement capacity hold at peak volume? The model sends each transaction through screening, a human review queue for flagged items and a settlement batch that closes on a clock. You read where transactions wait and how many miss the batch cut-off, with confidence intervals. Stocha can run this type of model today. It holds no financial-services regulatory approval.

What flows
Card payment, trade order, flagged transaction
What is scarce
Screening worker, matching engine slot, compliance reviewer
Where it waits
Screening queue, review desk queue, wait for batch close

Questions you can test

  • What peak volume can the screening step carry before delay grows?
  • How many reviewers does the desk need on a peak day?
  • What does moving the batch close time do to the oldest item in the batch?
  • How does one failed worker affect settlement time?
  • Is the limit in screening, review or settlement?

Financial services back-office case flow

Decision: which staffing and routing rule shortens turnaround for claims, loan files or legal matters? The model sends each case through review, approval and rework, with a specialist and a sign-off queue at each stage. You read turnaround with its confidence interval.

What flows
Insurance claim, loan file, account opening, compliance case
What is scarce
Intake clerk, specialist, senior specialist, approving manager
Where it waits
Intake queue, assessment queue, sign-off queue, rework queue

Questions you can test

  • How many specialists keep cases within the promised turnaround after a Monday surge?
  • Does cross-training clerks help more than hiring another specialist?
  • How much time do cases lose waiting for manager sign-off?
  • What does a higher rework rate cost in staff hours?
  • Should complex cases have their own queue?

Digital twin process

Decision: which layout or staffing change shortens the queue at a site’s busiest entrance? The model moves people or items between zones and holds them at the scarce robots, rooms or guides. You change one setting, rerun on the same random numbers and read the difference with its confidence interval.

What flows
Inbound item, visitor group, repeat visit
What is scarce
Robot, guided session room, guide, zone link
Where it waits
Receiving queue, link waiting area, room entrance queue

Questions you can test

  • How many robots does the site need before sorting stops holding up dispatch?
  • What does a robot fault do to the waiting items in the next hour?
  • How many guided rooms keep visitor waits short at a peak event?
  • Does a new zone layout remove the queue at the narrow link?
  • Which change helps most: another robot or a shorter handling step?

Field installation crew scheduling

Decision: how many crews and which shift pattern finish a rollout of meters, radios or cell equipment on time? The model assigns installation jobs to crews, vehicles and access windows, and sends failed installs back for a repeat visit. You read the completion time with its confidence interval.

What flows
Meter install job, radio install job, rework visit
What is scarce
Install crew, service vehicle, site access window, parts kit
Where it waits
Job backlog, wait for site access, wait for parts, rework backlog

Questions you can test

  • How many crews clear the job list by the planned finish?
  • Do longer shifts help more than a bigger crew?
  • How much does a missing part add to the time a job stays open?
  • What does a higher failed-install rate do to the rework backlog?
  • Should crews be grouped by town or share one pool?

Test a decision like these

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