Automation Solutions
Automation solutions are AI skills and agents built around a company's real procedures, systems, and handoffs, scoped to the lowest of five solution tiers that actually solves the problem. Most land at a reusable skill or a scheduled skill rather than a full agent. It is a fit for repetitive operational work such as intake, triage, routing, and recurring reporting.
Skills and agents built around your real procedures, systems, and handoffs, scoped to the smallest tier that actually solves the problem.
Pricing Fixed price, quoted from a full decomposition of the work after solution scoping. See full pricing →
Why this service exists
The best automation targets are rarely glamorous: intake, triage, routing, follow-through, and the status chasing nobody owns.
This is where tiers 2 through 4 get built. A skill is a reusable tool someone triggers when they need it. A scheduled skill runs on its own cadence with a human at the checkpoints. An agent works asynchronously, using tools and instructions to finish a task end to end.
We start at the lowest tier that solves the problem and only move up when the work genuinely calls for it. A skill that runs reliably for two years beats an agent that impresses in a demo and needs babysitting by month three.
What’s Included
- ☥ Workflow mapping and bottleneck identification
- ☥ Tier recommendation with the tradeoffs written down
- ☥ Integration with the systems your team already uses
- ☥ Human-in-the-loop checkpoints at the decisions that matter
- ☥ Logging, monitoring, and exception handling from day one
- ☥ Launch support and post-deployment tuning
Tier 2 → 4 · what actually changes
The difference between a skill, a scheduled skill, and an agent
Someone triggers it when they need it. Narrow, dependable, and cheap to keep alive. This is where most work should land.
Lowest cost to run
The same tool on its own cadence, with a human at the checkpoint. Partially async: nobody has to remember to run it.
Runs unattended
Given an objective, it picks its own tools and loops until the work is done. More capable, more surface area to monitor.
Highest oversight
Common Engagements
How this work usually shows up
Example scopes that turn this service into something tangible inside the business.
Intake & Routing
Engagement · 01
Capture incoming requests, classify them, and move them to the right owner with the context attached.
Automation Solutions
Scheduled Operations
Engagement · 02
Run recurring reporting, reconciliation, and follow-up on a cadence instead of on someone's memory.
Automation Solutions
Review Assistants
Engagement · 03
Draft recommendations, flag edge cases, and escalate anything the agent should not decide alone.
Automation Solutions
FAQ
Automation Solutions questions
The questions that come up most on intro calls, answered before you have to ask.
What kinds of work can actually be automated with AI?
The work that automates well is repetitive, rule-shaped, and high-volume: intake and triage, routing, data entry and re-entry between systems, document extraction, recurring reporting and reconciliation, status chasing, and first-pass drafting or review. Work that automates badly is judgment-heavy, low-volume, or depends on context that lives only in someone's head. MagicPill Labs scopes automation candidates against that distinction before quoting anything.
What are the solution tiers, and which one will we need?
MagicPill Labs scopes automation across five tiers: tier 1 is configuration of a tool you already own, tier 2 is a reusable skill your team triggers on demand, tier 3 is that same skill running on a schedule with a human at the checkpoints, tier 4 is an agent that completes tasks asynchronously using tools and instructions, and tier 5 is a full application. Most operational problems land at tier 2 or 3, and the recommendation is always the lowest tier that actually solves the problem.
How long before an AI automation pays for itself?
Payback depends on the volume of the work removed, which is why automation candidates are scored on hours saved per month before they are built. A tier 2 or tier 3 automation removing several hours of recurring work per week typically pays for itself within the first few months of operation; a tier 4 agent has a longer horizon because it costs more to build and carries ongoing model and monitoring cost. Any candidate whose payback cannot be estimated is a candidate that should not be built yet.
What happens when the underlying AI model changes?
Model changes are handled under Managed Solutions, which covers dependency and runtime updates alongside monitoring and incident response. Systems are built so the model is a swappable component rather than a hard dependency, and behaviour is checked against a set of known cases after any model change so drift shows up as a failing check rather than as a quiet decline in output quality.
Who owns the agents and automations you build?
Ownership is set in the engagement agreement, and the default is that the client owns the custom prompts, agent definitions, workflows, and configuration built for them. MagicPill Labs retains its own pre-existing internal tooling and reusable frameworks, licensed to the client for use within the delivered system, so nothing you depend on can be withdrawn.
How do you handle errors and edge cases in an automation?
Every automation ships with logging, monitoring, and explicit exception handling from day one, plus human-in-the-loop checkpoints at the decisions that carry real consequences. Cases the system is not confident about are escalated to a person with the context attached rather than guessed at, and failures surface as alerts rather than as silently missing work.