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hello@adherelabs.com · San Ramon, California · Serving clients across North America
Home / Services / AI & Automation / Workflow Automation for SaaS
01 — Automate

The operational work your roadmap never has room for.

Support triage, onboarding, billing recovery, usage alerting and churn signals — built as monitored workflows and AI agents inside your own stack. Your engineers keep shipping product.

What this is

Every SaaS company grows a second product nobody planned.

It is made of Slack threads, spreadsheets, half-finished internal tools and one person who knows how the refund process works.

It starts small. Someone checks failed payments each morning. Someone else copies new signups into a spreadsheet to see which ones activated. Support triages a queue by reading every ticket. A customer success manager keeps a private list of accounts that look wobbly. None of it is on the roadmap, all of it is load-bearing, and it scales linearly with customers — which is the one thing software is supposed to avoid.

This service is the systematic version of that work. We map the operational surface of your business, decide what should be a deterministic workflow, what genuinely needs a model, and what should stay human — then build it as monitored, versioned automation running in your own cloud accounts next to your product.

Two categories, usually built in this order. Internal ops first, because the risk is contained and the payback is immediate: alerting, data sync, reporting, provisioning, reconciliation. Customer-facing agents second, because anything a customer talks to needs the retrieval, the guardrails and the escalation paths to be right before it goes live.

What you get

Where automation pays for itself first.

01

Support triage and deflection

RAGpgvectorSlackNotion

An agent reads every inbound ticket, classifies it by area and severity, attaches the account context a human would have gone looking for, and routes it. Where the answer already exists in your documentation, changelog or a past resolved ticket, it answers directly with a citation. Where it does not, the ticket reaches the right engineer already tagged and enriched.

  • Classification and severity scoring on first contact, with account context attached
  • Retrieval over your docs, changelog and resolved tickets — answers with sources
  • Draft replies for agents to approve rather than fully autonomous sends, if you prefer
  • Escalation rules for churn-risk accounts, outages and anything account-specific
02

Onboarding and activation automation

Postgresn8nEmailIn-app

Activation is a sequence of milestones, and most teams only measure the last one. We instrument the steps that actually predict retention for your product, then automate the nudges, the provisioning and the internal handoffs around them. An account that stalls before its first integration gets a different intervention than one that never invited a teammate.

  • Milestone events defined and instrumented in your product database
  • Behavior-triggered onboarding sequences across email and in-app messaging
  • Automated workspace provisioning, sample data and environment setup
  • Internal alerts when a high-value account stalls, routed to a named owner
03

Billing, dunning and revenue recovery

StripeWebhooksQuickBooks

Failed payments are the quietest form of churn. A card expires, the retry fails, an email lands in a spam folder, and an otherwise happy customer disappears. We build the dunning ladder properly on Stripe webhooks — retry timing, escalating messaging, in-app banners, grace periods and entitlement changes that match your commercial policy rather than the default.

  • Stripe webhook handling with idempotency and full event replay
  • Dunning sequences with retry scheduling, in-app banners and human escalation
  • Entitlement and access changes that follow your grace-period policy exactly
  • Revenue reconciliation between Stripe, your database and your accounting system
04

Usage alerting and churn signals

PostgresSlackDashboards

Usage data usually exists and is usually unread. We turn it into signals that reach a person while there is still time to act: seats going unused before a renewal, an account whose weekly active count halved, a customer approaching a plan limit, an enterprise trial that has gone quiet. Each signal carries the account, the evidence and the suggested next step.

  • Usage and health scoring computed from your own product events
  • Expansion signals — limit approaching, seats maxed, new team adoption
  • Risk signals — drop-off, unused seats, support pattern, renewal proximity
  • Slack and email digests with the context needed to act, not just a red number
05

Internal ops and agent infrastructure

n8nAWSGoogle CloudMCP

The unglamorous layer: scheduled data syncs, report generation, environment provisioning, compliance evidence collection, cross-tool notifications. Where agents need to take actions in your systems, we expose those systems through Model Context Protocol servers with scoped credentials, so an agent's capabilities are defined by the tools it is given rather than by hope.

  • Self-hosted workflow runtime in your cloud, with retries and dead-letter queues
  • MCP servers exposing internal systems to agents under scoped, auditable access
  • Monitoring, alerting and cost visibility on every workflow and model call
  • Runbooks, architecture notes and a handover your on-call engineer can use
How it connects

Automation is half of it. The other half is product.

An agent is only as good as the systems it plugs into. When your stack can't support the automation, we build the stack.

SaaS operations break in places a generic automation shop rarely looks. Onboarding that has to work without a call. Billing edge cases that only surface at renewal. A support queue where the tenth similar ticket costs exactly as much as the first. We scope automation against those realities, and we are deliberately conservative about what runs unattended: anything touching billing, permissions or customer data gets an approval step or a deterministic fallback rather than a hopeful prompt.

The same is true of the engineering side. Plenty of SaaS operational problems are not automation problems at all — they are missing product surface. When the answer is an admin tool, a webhook receiver, a proper events table or an in-app assistant, our software team builds it in your codebase. We integrate what already exists, and build what doesn't.

StripeSlackNotionPostgresSupabasen8nAWSGoogle CloudVercelMCPLangGraphOpenAIAnthropicpgvectorOAuth 2.0Webhooks
The loop

The work that comes back every single month.

Nothing here is a project. It is a circuit your customers ride around, over and over, for as long as they stay.

Fig. 01 — Customer lifecycle loop
Signup trial starts Onboarding activation nudges Usage signals risk + expansion Support triage answered from docs Billing & renewal dunning recovery Your team exceptions only escalations only repeat
The loop runs whether or not anyone is watching it, which is exactly the problem when it is held together by people. Automating a step here does not remove your team from the customer — it removes them from the part of the step that is identical every time. What reaches the middle of the diagram is the small share of cases where a judgment call actually changes the outcome.
How we work

Contained risk first, customer-facing second.

Phase 01 — Audit

Map the manual surface

We sit with support, success and ops and list every recurring task, who does it, how often, and what breaks when they are away. The output is a ranked roadmap by payback and risk, and it is yours to keep.

30-min call · roadmap delivered
Phase 02 — Build

Internal ops, then agents

Deterministic workflows go first — sync, alerting, reconciliation, provisioning. Model-driven agents come after, with retrieval grounded in your real documentation and escalation paths tested before launch.

Typically 3–6 weeks
Phase 03 — Operate

Monitor, measure, hand over

Every workflow reports success rate, latency and cost. We review deflection quality and false escalations, tune the logic, and document everything so your team can take the whole thing over whenever it wants to.

Ongoing partnership
Common questions

Before you ask.

We already have engineers. Why bring in an outside team for this? +

Because internal ops work never wins a roadmap argument against customer-facing features, and it never will. Your engineers keep shipping product while we build the operational layer around it. Everything we write lands in your repositories and your infrastructure, reviewed by your team, so it is not a parallel system nobody understands.

Where does the automation run and who owns it? +

In your cloud accounts, under your credentials, on your infrastructure. Workflows run on a self-hosted n8n instance or as services in AWS or Google Cloud alongside your existing stack. Source, configuration and runbooks are handed over in full. You own every account, every workflow, every line of code and every byte of your data.

Can an AI agent touch production data safely? +

Only with boundaries that are enforced outside the model. Agents get scoped credentials, read-only access wherever reads are enough, and tool definitions that limit what an action can do rather than trusting the model to behave. Writes that affect money, entitlements or customer records run through explicit approval or an idempotent, reversible job.

How do you deflect support tickets without annoying customers? +

By answering only what the agent can answer from your real documentation, and routing the rest immediately. Deflection built on retrieval over your own docs, changelog and past resolved tickets gives specific answers with links. Anything uncertain, angry or account-specific goes to a human on the first message, not the fourth.

Do you build inside our product or around it? +

Both, depending on where the work belongs. Support triage, billing recovery and internal alerting usually sit around the product as workflows and services. In-app assistants, onboarding checklists and usage-driven prompts belong inside it, and our software team ships those in your codebase with your review process.

How do you decide what should run without a human? +

By blast radius. Reversible, low-stakes work — drafting replies, tagging tickets, syncing records, sending reminders — runs unattended. Anything that touches billing, permissions, customer data or an irreversible action gets a human approval step or a deterministic fallback. We would rather automate less and have you trust every run than automate everything and have you checking it.

The trade you keep making

Every internal tool you ship
is a feature you didn't.

Start here

Name the task your team does every single day.

Bring one recurring operational chore to a 30-minute call. We will tell you honestly whether it should be a workflow, an agent, a product change, or left alone — and give you the ranked roadmap for the rest.

Roadmap delivered · whether or not you build with us