Full-Lifecycle Process Automation
Flex Solutions delivers business process automation services for one specific process at a time, the one your ops team already knows by heart because someone has to run it manually every week. AI process automation, done as an engineering discipline instead of a stack of triggers, means that process gets automated end to end on infrastructure built to survive restarts, retries, and the exception nobody planned for.
Business process automation with AI that survives restarts and retries.
Can You Start Without Committing to a Full Engagement?
Yes. A one-week process audit gives you a time study and a scored recommendation on what to automate first, before you commit to a 6 to 12 week build. We sit with the team that currently owns the process, map every step, time every step, and surface every exception.
You leave with one process scoped for automation, a documented reason for setting the others aside, and a fee letter, whether or not you continue past that point.
How We Work: AI Process Automation Step by Step
- 01
Process audit
Every step of the process gets mapped and timed, and every exception gets surfaced, before a line of automation code is written.
Process mapTime studyScope freezeWEEK 1 - 02
Eval and happy path
An eval suite is seeded from real cases before automation begins, and the happy path runs end to end on staging.
Eval harnessStaging pipelineCost projectionWEEK 2-6 - 03
Edge cases and handoff
Exception handling, human review queues, and monitoring get built out, and the automation ramps to a small share of live volume.
Review queueDashboardsRamp planWEEK 6-10 - 04
Full rollout and training
The process ramps to full live volume, your ops team is trained to run and edit it, and a runbook is handed over with a 30-day support tail.
Full rolloutOps trainingRunbook30-day supportWEEK 11-12
Deliverables From Our Process Automation Pod
Most AI automation is a trigger flow that breaks every Tuesday. We build durable, evaluated, observable automations for the long-running processes your operations team runs by hand: onboarding, invoice reconciliation, support triage, content moderation, and contract review. Agents where they help. Deterministic code where they do not.
A written process map and time study, with the recommended process to automate first.
A working automation for that process, end to end, not a partial flow that still needs daily checking.
Durable execution on Temporal, Inngest, or n8n, so it survives restarts and retries.
An eval suite for every AI step in the pipeline, run on every change.
Human-in-the-loop review queues where confidence drops below an agreed threshold.
Cost, latency, and cycle-time dashboards from day one.
A runbook and training for your ops team to operate it after handover.
Capabilities - Inside the Engagement
- 01
Process discovery
A workshop with the team that owns the process today, mapping every step and every exception before any automation code exists.
- 02
Durable workflows
Temporal, Inngest, or n8n handle long-running, retryable processes, surviving deploys and partial failures without losing their place.
- 03
Agentic steps
LLMs are used only where the work is unstructured, such as classification or extraction, with structured output your code can act on directly.
- 04
Human handoff
Confidence thresholds route uncertain cases to a review queue with an edit-and-approve flow, so a person sees the cases that genuinely need one.
- 05
Integrations
Salesforce, HubSpot, Stripe, Zendesk, Slack, Notion, Airtable, and Gmail connected through first-party APIs, with documented rate limits and retries.
- 06
Observability
Every run traced, every AI call logged with tokens and cost, every override recorded, with cycle time as the metric that matters.
The AI Process Automation Stack We Use
These are opinions formed by running automations in production, not vendor preference. We choose the stack that survives a Friday at 5pm, not the one that looks good in a demo.
- + WORKFLOWSTemporalInngestn8nTrigger.dev
- + AIClaudeGPT-4 / 5GeminiOpenRouter
- + EVALSBraintrustPromptfooInspectcustom harnesses
- + OPSSentryOpenTelemetryGrafanaPostHog
Teams evaluating durable workflow engines directly can also reference Temporal’s own documentation and n8n’s workflow documentation as a starting point.
Business Process Automation vs. the Alternatives: How We Decide
| Comparison factor | Flex Solutions | DIY With Zapier or Make | Hiring an Ops or RevOps Engineer |
|---|---|---|---|
| Time to start | 1-week process audit, then a scoped 6 to 12 week build | Immediate, but rebuilt every time the process changes | Weeks to months of hiring and ramp-up |
| Cost structure | Fixed fee or capped monthly retainer, scoped after the audit | Per-seat SaaS pricing plus the hidden cost of constant fixing | Salary, equity, benefits, indefinitely |
| Risk if the fit is wrong | Engagement ends at a scoped point, low sunk cost | Flow breaks on the first long-running or exception-heavy case | A bad hire costs months to unwind, and the process still needs building |
| Best fit | A specific, long-running, exception-heavy process worth automating properly | A short-lived, low-stakes trigger with no real exception handling | Ongoing operational ownership across many processes, not one build |
We default to the audit-first model because it surfaces the real shape of the process, and its real exceptions, before anyone commits to a full build. If a simple trigger genuinely covers your case, we will say so instead of selling you more than you need.
Not sure which process is worth automating?
Numbers From Processes We’ve Automated
Zapier and Make are built for simple, short-lived triggers. A durable workflow engine like Temporal, Inngest, or n8n is built to survive restarts, retries, and partial failures across a process that runs for hours, which is the difference between an automation that quietly stops and one that picks back up where it left off.
Every AI step ships with an eval suite and a confidence threshold. Cases below that threshold route to a human review queue instead of shipping unreviewed, which is how the override rate stays under 2% once an automation is tuned.
Long-running, exception-heavy processes with a meaningful unstructured component are the best fit, such as customer onboarding, invoice reconciliation, support triage, content moderation, or contract review. The right candidate is confirmed during the Week 1 process audit, not assumed upfront.
Yes. Temporal and Inngest can run self-hosted, and n8n can be deployed on your own infrastructure, with integrations built on first-party APIs so the automation fits inside your existing security posture.
A process change is treated like a code change: reviewed, tested against the eval suite, and shipped. Your ops team is trained to make routine edits directly, so a minor change does not require bringing Flex Solutions back in.
We quote engagements as a fixed fee or a capped monthly retainer, using the same transparent pricing model we apply across all Flex Solutions services, scoped immediately after your Week 1 process audit rather than estimated upfront.
Full-Lifecycle Process Automation Starts With an Audit
Book a one-week process audit. You will leave with a time study, a scored recommendation, and a fee letter, whether or not you hire us for the full build.