Less manual work, with controls
AI and Business Automation
Palmate Solutions implements business automation that reduces repetitive work: data synchronization, notifications, approval routing, and AI-assisted steps where a model can draft, classify, or extract — with a human still accountable for outcomes. We do not sell autonomous agents as a substitute for process design. We automate the paths you can describe, measure, and roll back.
Problems this work solves
People are the integration layer
Staff copy fields between tools because nobody owned the workflow. Automation should remove that tax, not add another dashboard they must babysit.
AI was added where rules would do
If the policy is deterministic, use rules. Models are useful for messy text, classification, and drafts. Using a model for a tax calculation is the wrong kind of clever.
No audit trail
When something auto-sends a customer message, you need to know why. We log inputs, prompts or rule hits, and the action taken.
Automation that cannot be paused
A job that emails 4,000 customers with no kill switch is a liability. We build enable flags, rate limits, and dry-run modes.
Who it is for
- Operations managers drowning in status updates and re-keying
- Teams that want AI to draft or classify, not to silently change money or inventory
- Businesses with clear SOPs that are still executed by hand
- Companies connecting notifications, CRMs, and internal tools into one flow
What Palmate can provide
Workflow automation
Triggered jobs, scheduled syncs, and approval chains implemented in code you can test — not an unowned zap.
AI-assisted steps
Classification, extraction, summarization, and draft generation with evaluation sets and human review where the cost of error is high.
Notifications and operational alerts
The right person hears about a failed payment or a stuck order without drowning in noise.
Data synchronization
Keep records aligned across systems with conflict rules that are written down.
Typical workflow
- 01
Map the current path
We watch the real process, including the unofficial workarounds. Automation that ignores workarounds will be bypassed.
- 02
Separate rules from models
Deterministic policy stays in code. Models get a bounded job and a quality bar.
- 03
Pilot with a kill switch
A subset of traffic or a single team. Metrics for time saved and error rate beat a demo.
- 04
Expand and observe
Once the pilot is boring, we widen scope and keep the logs.
Common use cases
Order exception handling
Route only the weird cases to humans; let the routine cases flow through integrations.
Inbox classification and draft replies
Tag incoming requests and draft a response for an operator to send. The operator remains the sender of record.
Document and invoice capture
Extract fields from semi-structured files, then require confirmation before writing to accounting or ERP.
FAQ
Will you put a chatbot on our website?
Only if it has a job, a fallback to a human, and content it is allowed to use. A generic chat widget that hallucinates policy is worse than a good contact form.
Do we need a large language model?
Not always. Many automations are API workflows and rules. We recommend a model when language or unstructured input is the bottleneck.
Where does company data go?
That depends on the vendor and contract. We document data flows and can keep processing on infrastructure you control when that is a requirement.
How do you measure success?
Hours removed from a named process, error rate, and time-to-recovery when automation fails — not ‘AI adoption’ as a vanity metric.
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Next step
Discuss ai & automation
Share the current system, the constraint, and the outcome you need in the next quarter. We will say if Palmate is a fit.