Tealfabric

ProcessFlow execution

Trigger → connect → AI → push → review

01 Trigger02 Integrate03 LLM04 Push05 Audit

Process: vendor_intake_enrichment · execution_id: pf_8f2a

AI agent chat

sync · agent trigger

“Enrich vendor Acme Parts — pull CRM account and classify industry.”

WebApp form

sync · form submit

{ "vendor_name": "Acme Parts", "tax_id": "FI-12345", "contact": "ops@acme.fi" }

Parent process

async · process-to-process

onboarding_pipeline → queue subflow · cursor: batch 12/40

step: receive_input → merged process_data.vendor

Simulated flow — controlled step code from AI chat, WebApp, or parent workflow through connections and AI to downstream systems

Controlled automation

“Write real code. Run inside safety rules—prototypes become live workflows without a rewrite.”

Platform

Process Automation — workflows built step by step, in a safe sandbox

Turn know-how stuck in people's heads into workflows you can review—step-based ProcessFlow with JavaScript or TypeScript. Start from APIs, WebApps, schedules, and AI; call connections, Datapools, AI steps, and files inside platform safety rules.

Adoption context

You need this when
Onboarding, exceptions, and handoffs outgrow spreadsheets and inbox threads—you need reviewable steps, records, and owners.
Often bundled with
Integrations for live workflows on one platform.
Not required if
A single controlled connection retry or intake trigger is enough for your first workflow—you can add full ProcessFlow modeling later.

ProcessFlow is how work moves through Tealfabric—not a separate scripting tool beside the platform.

Teams usually choose between no-code builders that are hard to extend, custom scripts that are fragile and insecure, or heavy enterprise workflow software disconnected from data and system connections.

ProcessFlow offers a third path: step-based automation with real code, inside a sandbox that enforces safety. Every step runs in a controlled environment where code can use platform services but cannot bypass platform boundaries or security rules.

  • Step-based automation with real code—inside a sandbox that enforces safety
  • Not a separate scripting tool: how work moves through schedules, WebApps, APIs, and Datapools
  • JavaScript and TypeScript per step—with platform services built in
  • Sequential and parallel strategies; immediate for speed, queued for scale
  • Start from API, WebApp, cron, events, webhooks, or another workflow
  • Connections, Datapools, files, credentials, OCR, and AI from step code—no secrets in snippets
  • Workflow-to-workflow composition, batch continuations, and structured step errors
  • Run history, step logs, and queue visibility alongside platform monitoring

Production patterns

Operations teams ship automation without standing up separate job runners.

The patterns below are illustrative examples—common starting points, not a fixed catalog.

  1. webhook → OCR
    → CRM · DataPool

    01. Invoice processing

    Webhook receives a file → OCR extracts text → validation step → CRM connection updates the account → result written to a Datapool.

  2. event trigger
    parallel checks

    02. Customer onboarding

    Event trigger on new user → parallel checks (identity, compliance, provisioning) → notification step → WebApp shows live status.

  3. cron → ERP
    TypeScript transform

    03. Nightly operations

    Scheduled trigger → pull from ERP connection → transform in TypeScript → batch write to Datapool → summary email to ops.

  4. WebApp sync
    async queue

    04. Self-service portal

    WebApp submits form → workflow validates immediately → background workflow handles heavy work → user checks queue status.

  5. PDF OCR
    LLM classify

    05. Document intelligence

    Upload to platform storage → PDF OCR step → AI summarization → route by classification.

End-to-end flow

AI chat, WebApp, or parent workflow starts a controlled multi-step run.

A vendor intake workflow receives input from AI, a self-service form, and an upstream onboarding pipeline. Steps call Salesforce, run AI classification, push to HubSpot, write to a Datapool—and leave step logs and queue history for operators.

ProcessFlow execution

Trigger → connect → AI → push → review

01 Trigger02 Integrate03 LLM04 Push05 Audit

Process: vendor_intake_enrichment · execution_id: pf_8f2a

AI agent chat

sync · agent trigger

“Enrich vendor Acme Parts — pull CRM account and classify industry.”

WebApp form

sync · form submit

{ "vendor_name": "Acme Parts", "tax_id": "FI-12345", "contact": "ops@acme.fi" }

Parent process

async · process-to-process

onboarding_pipeline → queue subflow · cursor: batch 12/40

step: receive_input → merged process_data.vendor

Simulated flow — controlled step code from AI chat, WebApp, or parent workflow through connections and AI to downstream systems

Capabilities

Composable steps, flexible timing, and operable execution.

Design in the platform library, test before go-live, and run from anywhere your business needs work to start.

  1. steps · conditions
    merge semantics

    01. Step-based workflow design

    Multi-step workflows with conditions, branching, and shared state.

    Model work as a sequence of steps—each runs logic that validates data, calls a system, transforms a file, or decides what happens next. Output from each successful step flows into shared state for later steps.

  2. JS · TS
    per step

    02. JavaScript and TypeScript

    Choose the language per step—meet teams where they already work.

    JavaScript for JSON-centric transforms; TypeScript for typed step logic and safer refactors. The platform detects or respects the language you choose per step.

  3. sequential · parallel
    sync · async

    03. Sequential, parallel, immediate, and queued

    Strict order when steps depend on each other; parallel when branches are independent.

    Run now and wait for an answer, or queue and check later. Same workflow definition—choose timing per run. Suited to approvals, enrichment chains, and overnight imports alike.

  4. API · WebApp
    cron · webhook

    04. Start from anywhere

    API, WebApps, schedules, platform events, webhooks, and workflow-to-workflow.

    External systems start runs with platform API credentials. User-facing apps call workflows immediately or in the background. Cron, events, and webhooks start runs automatically—one workflow can queue another without blocking.

  5. safety rules
    platform-scoped

    05. Safe sandbox guardrails

    Real code inside a controlled environment—not raw server access.

    Step code runs in an isolated environment with approved platform services. Shell execution, raw network calls, direct database drivers, and environment tampering are blocked at save time and at runtime.

  6. integrations
    DataPool · LLM

    06. Platform services built in

    Connections, Datapools, files, credentials, OCR, AI, and notifications from step code.

    Every step starts with injected context and service handles—platform scope, workflow input, configured connections, internal API, database, Datapools, files, secrets, logging, and document intelligence.

  7. workflow chains
    batch cursor

    07. Workflow composition and batch work

    Fan-out sub-workflows, event chains, and cursor-based continuations.

    Workflows can trigger other workflows for reuse and event-driven chains. Iterate over bounded lists in one step, or hand off the next batch by queuing another run with a cursor—large datasets without overloading a single execution.

  8. step logs
    queue · history

    08. Built to be operated

    Step logs, run history, queue visibility, and structured error codes.

    When something fails at 2 a.m., teams see which step, which run, and why—not a black box. Workflow activity sits alongside connections, security, and data history in one place.

Sandbox services at runtime

Authors write normal step logic. The sandbox supplies context, services, and safety rules so snippets stay small and focused. Configurable capability profiles let operators tighten or broaden what a run may do.

Workflow input and context

Read trigger payload and accumulated step output

Platform scope

Every operation stays inside your platform account

Integrations

Call configured connections to external systems

Internal API

Reach platform APIs with execution authorization

Platform database

Query and update transactional data safely

Datapools

Insert and update operational datasets from steps

Files

Read and write platform-scoped storage

Credential store

Retrieve secrets at runtime—never hardcoded in snippets

Logging

Write execution logs for debugging and review

Document intelligence

PDF and image OCR from platform files

AI assistance

AI-powered steps within your platform rules

Notifications

Email and messaging from workflow logic

Languages per step

JavaScript

Modern step code, JSON-centric transforms, async service calls

TypeScript

Typed step logic, larger teams, safer refactors

Pairs with Integrations

ProcessFlow decides the steps; Integrations connect to your systems. Configure Salesforce, SFTP, or email once—call from any step without credentials in code. Combine multiple systems in one controlled workflow and land outputs in Datapools for reporting and follow-on workflows.

Integrations & Connectors

Turn business rules into production automations

See ProcessFlow with sandbox safety rules, triggers, and connection steps.

We walk through step design, immediate and queued runs, stored credentials, AI steps, Datapool writes, and run history—on the same platform as connections and access controls.

Book a demoStart a pilotIntegrations

Pilots start with one live workflow—system connections, steps, and full history.