Alexis Degler

Building AI systems that run real businesses. Sharing what works, what breaks, and what I'd do differently.
Jakarta-based, global tools

[Alexis Degler @Alexis_Degler]

Your best people are buried in reconciliation, manual data entry, and approval chasing across three systems. The reflex is to hire — to paper over broken workflows with more headcount.
But more hands on a broken process just multiplies the drag. Cycle times stretch, margin...

[Alexis Degler @Alexis_Degler]

The goal is not replacing your ops team. It is giving them digital workers so they can focus on exceptions and strategy instead of data entry. We design and deploy these systems for mid-market teams. See how we work: https://t.co/d2JzegDLdx

[Alexis Degler @Alexis_Degler]

Most ops teams use AI to write emails. That is a waste. AI agents can actually execute back-office workflows end to end. Here are 4 workflows you can automate this week to stop pushing paper.

[Alexis Degler @Alexis_Degler]

4. Inventory backorder comms. Agent monitors your warehouse stock feed. When an item drops below zero, it queries the PO tracker, calculates the ETA, and drafts a personalized delay email to every impacted account for you to hit send.

[Alexis Degler @Alexis_Degler]

If you are a mid-market ops team trying to deploy AI without violating SOC2 or losing your CFOs trust, you need an architecture built for compliance from day one. RECLAIM builds auditable AI automation systems. See how: https://t.co/d2JzegDLdx

[Alexis Degler @Alexis_Degler]

Most finance AI pilots die in security review. If you want automation your CFO and IT actually approve, you cannot use open web LLMs. You need strict governance. Here is the exact architecture to build auditable AI for finance ops.

[Alexis Degler @Alexis_Degler]

3. Force human approval gates. The AI should never post to the GL or execute wires on its own. Build a UI that outputs the proposed action and confidence score. Require a finance controller to click Approve. The AI prepares, humans execute.

[Alexis Degler @Alexis_Degler]

If your ops team is manually moving data because leadership does not trust the AI, we can help. RECLAIM builds governed AI automations for mid-market finance and ops. https://t.co/d2JzegDLdx

[Alexis Degler @Alexis_Degler]

Most finance automation fails because ops can't audit it. Here is how to build governed AI workflows your CFO will actually approve.

[Alexis Degler @Alexis_Degler]

Step 3: Route by confidence. If the model is 98% sure, post to NetSuite. If it is 80%, drop it into an Ops queue for human review. You get speed without losing financial control.

[Alexis Degler @Alexis_Degler]

If your operations team is drowning in repetitive data work, you do not need to hire your way out of it. You need to build your way out. We build custom AI systems for ops teams. See how we do it: https://t.co/d2JzegDLdx

[Alexis Degler @Alexis_Degler]

Mid-market ops teams do not need more headcount. They need a ruthless process audit. Most ops professionals are buried in manual work that an AI sequence could handle. Here is exactly how to find and automate those hidden bottlenecks.

[Alexis Degler @Alexis_Degler]

Step 3. Connect the pipes. You do not need a massive digital transformation. Run a scheduled trigger from your database into an AI model using Zapier or Make. Have the output pushed directly to a Slack channel. Start with a 30-day test. Measure the hours saved.