How Chip Works
Not a chatbot.
An engineer that never clocks out.
Chip connects to your systems, learns from every case your team has ever closed, and responds to new events in real time, classifying, routing, investigating, and closing the loop without waiting to be asked.
Connect & Learn
Ingests 6+ months of your case history before handling its first ticket.
Event-Driven Engine
Every new event re-triggers analysis, continuously, in real time.
Custom Intelligence
Build labels, routing rules, and automations on top of your caseload.
Connects to your stack
Support
Engineering
Documentation
Communications
01 · Connect & Learn
Chip arrives already knowing six months of your history.
On day one Chip connects to your support, engineering, and communication systems and ingests every case your team has closed: what was tried, what worked, what failed, how long it took. It runs autonomous post-mortems across the full dataset before it handles a single live case.
- Indexes resolved cases, engineering tickets, and conversation threads together.
- Runs post-mortems agenically, with no manual tagging or annotation required.
- Identifies recurring patterns, common root causes, and previously missed signals.
- The moat is your data. It compounds with every case closed.
“A team building on Claude or Mistral has a capable model and zero outcome history. Chip has six months of your specific case resolutions, failures, and patterns before it handles its first ticket. That's not a head start. That's a different product.”
15,383 cases · post-mortems complete
Classify intent · match similar cases · set resolution hypothesis
"Does this new message confirm or challenge the current path?"
Re-evaluate impact · revise ETA · update customer proactively
Run post-mortem · index outcome · close loop with customer
02 · Event-Driven Engine
Every new event re-triggers analysis. Continuously.
Chip runs on the Waypoint AI Agentic Automation Platform, a real-time, event-driven architecture where every new signal from your connected systems triggers a fresh round of analysis. Not a batch job. Not a nightly sync.
When a customer sends a new message, Chip doesn't just append it to a thread. It asks: “Does this new information confirm or challenge the current resolution path?” If it challenges it, the analysis updates. If an engineer adds context to the ticket, the customer gets a proactive update.
- Triggers fire on case creation, new messages, status changes, ticket updates, and deployments.
- Each trigger re-runs the relevant analysis nodes, not the whole pipeline.
- Resolution confidence is tracked continuously and escalated automatically when it drops.
- Chip never waits to be asked. If something changes, it already knows.
03 · Custom Intelligence
Build an intelligence layer on top of your caseload.
Chip can define and apply custom labels across your entire case history, not just new cases. Those labels drive routing, root cause grouping, escalation rules, and trend detection. You describe the logic in plain language. Chip applies it at scale.
- Define custom labels that map to your specific product, team, and failure modes.
- Retroactively apply labels to past cases to instantly surface patterns that were invisible.
- Wire automations to labels: route, escalate, notify, or open tickets automatically.
- Run trend reports across any label dimension. Which issues are accelerating?
Labels and automations are built on the same pipeline architecture Chip uses internally, so anything Chip can do, you can wire up for your own workflows.
The path to autonomy
From recommendation to full autonomy, on a defined, measurable path.
Every prospect asks about the journey from assistant to autonomous. The answer is explicit, including where it ends.
Chip recommends. Agents decide.
Chip surfaces its reasoning, suggested next steps, and relevant case history. Agents review before any action is taken.
Track acceptance rate.
When agents accept Chip's response without modification consistently, Chip is ready to act without the review step.
Chip resolves cases autonomously.
Agents focus on what genuinely requires human judgement: complex relationships, novel situations, cases with commercial stakes.
Chip fills the Tier 1 role.
"The business goal is for Chip to fill one seat of a Tier 1 rep." That seat doesn't get backfilled.
For your support engineers, this means moving from the work AI should do to the work only they can. Your team doesn't shrink. It moves up.
Why not build it yourself?
Building on Claude or Mistral gives you a model. Not a product.
The objection is common. The answer is simple.
| Attribute | DIY on Claude / Mistral | Chip |
|---|---|---|
| Time to first value | 4–6 months | First week |
| Case knowledge on day one | Zero (starts blank) | 6+ months of your resolved cases |
| Integration depth | Whatever you wire up | Salesforce, Zendesk, Jira, Slack, GitHub. Pre-built. |
| Accuracy over time | Static; you retrain it. | Compounds with every case closed |
| Maintenance burden | Ongoing. You own it. | None. Waypoint runs it. |
| Complex / multi-system cases | Often fails | Reasons across your full case history |
Ready to see it on your case history?
We bring your data in on day one. First session, real outcomes.