Process Mapping
Map the real decisions, owners, and exceptions. Turn a messy workflow into a shared model before a single endpoint is built.
- 01 Define the starting event
- 02 Make the exception path visible
THE PRACTICAL PROCESS PLAYBOOK
Map it. Automate it. Batch it at scale.
Practical guides for the work your team repeats. Connect process maps, automation, image and file batches, local LLMs, and frontier AI with a clear, dependable API design.
- Core disciplines
- 06
- Practical playbooks
- 10
- Connected approach
- 01
CONNECTED SYSTEMS
DESIGN PATTERN
Input → Output
The processing surface
Six disciplines.
Six disciplines.
One connected approach.
Follow the whole path: define the work, prepare the inputs, process the batch, and verify the result. Start with the discipline your team needs today.
Process Automation
Connect triggers, durable state, approval gates, and recovery. Build automation that can explain what happened after an interrupted run.
invoice.received
event
nightly.reconcile
schedule
contract.approve
approval
Batch Process Images
Plan repeatable resizing, format conversion, metadata handling, and quality checks. Preserve originals and account for every output variant.
ORIGINAL → TRANSFORM → VERIFIED ASSET
Batch Process Files
Bring structure to documents and CSVs. Separate parsing from validation, track rejected items, and reconcile the final delivery.
› collect the input manifest
› parse supported file types
› validate the required fields
› review unresolved records
› publish accepted outputs
Local LLM Batch Jobs
Build queues for local inference. Define a data boundary, validate structured outputs, and measure throughput on a representative task.
WORKLOAD DESIGN
Bounded batches
ACCEPTANCE RULE
Validate first
Frontier Model AI Processing
Evaluate demanding AI tasks and route by evidence. Keep acceptance standards, data policy, and budget limits ahead of model hype.
evaluation
evidence
cost limits
Explore frontier AI {
"process": "documents.intake.v1",
"input_manifest": "manifest-001",
"policy": {
"validation": "required",
"on_ambiguity": "human_review",
"max_attempts": 3
},
"output": {
"include_item_results": true,
"publish_after_validation": true
}
}A reference pattern for your own implementation. Read the contract before choosing the runtime.
Ship it your way
A clear contract.
A better system.
Make accepted intent, execution state, and business outcomes understandable from the very first request.
Business Process APIAsynchronous runs, permissions, versions, and outcomes.Self-Hosted APIData boundaries, worker access, and recovery ownership.Open the reference docsPremium AI Credits
Count outcomes.
Understand the cost.
Separate usage, retries, and review from the price of a request. Plan around the work you actually accept.
01 / UNDERSTAND
AI credits explained
Connect provider-defined billing units to your workload and acceptance rule.
Read the guide 02 / COMPAREChoose a processing model
Compare rules-first, local inference, and hosted AI without fictional price plans.
Read the guide 03 / MEASURECost per accepted job
Follow a worked example with explicit assumptions and a reconciled result count.
Read the guideThe Process Playbook
Less theory.
More useful next steps.
Ten deep dives into the systems behind repeatable work.
Browse all articlesBatch file processing: validate, transform, and reconcile every file
Build a file pipeline around explicit schemas, immutable inputs, item-level errors, and verifiable delivery.
Business process API design: make long-running work understandable
Model asynchronous runs, business state, versioning, authorization, and outcomes through a clear API contract.
Batch image processing: a repeatable pipeline from originals to delivery
Plan image transforms, metadata rules, output naming, and quality checks before processing an entire library.
A little clarity
Good questions.
Clear answers.
Start with the decision, then find the right playbook.
What is a process API?
A process API is an interface for submitting, observing, or coordinating a business workflow. Start with a defined outcome, stable run identity, and documented state transitions. The API design guide develops a reference pattern.
Where should I start with process automation?
Start by mapping one recurring task with an observable outcome. Define its owners, required inputs, and exception path, then automate a narrow transition. The mapping guide provides a practical starting point.
How are batch image and batch file processing different?
Image pipelines focus on composition, dimensions, formats, and visual quality. File pipelines focus on parsing, schemas, normalization, and accepted records. Both benefit from item-level manifests and explicit delivery rules.
How should I choose between local and frontier models?
Define the task, data policy, and acceptance test first. Compare representative outputs, operating effort, and cost under the same rule. Review the local LLM guide and frontier routing guide together.
Does ProcessAPI.com provide API keys or sell AI credits?
ProcessAPI.com is a technical publication and implementation reference. The documentation contains design examples, and the pricing page explains cost planning. There is no account, hosted processing endpoint, or checkout on this site.
Make the next step a clear one
Build the process.
Not the guesswork.
Start with a map, explore the reference patterns, or open a playbook for the work in front of you.
Open the reference docs