# Building Jarvis Pro: Route first, answer later

DevFeed: [Building Jarvis Pro: Route first, answer later](<https://devfeed.tech/articles/building-jarvis-pro-route-first-answer-later-1251.md>)

Original publisher: [Read original article](<https://engineering.grab.com/jarvis-pro-route-firsr-answer-later>)

Author: Christian Coffrant

Published: 2026-08-21T00:00:00Z

Content type: article

Language: en

Sources: [Grab Tech](<https://devfeed.tech/sources/grab-tech.md>)

Topics: [AI Chat](<https://devfeed.tech/topics/ai-chat.md>)

Tags: [account-management](<https://devfeed.tech/tags/account-management.md>), [ai](<https://devfeed.tech/tags/ai.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [business](<https://devfeed.tech/tags/business.md>), [classification](<https://devfeed.tech/tags/classification.md>), [data](<https://devfeed.tech/tags/data.md>), [engineering](<https://devfeed.tech/tags/engineering.md>), [evaluation](<https://devfeed.tech/tags/evaluation.md>), [llm](<https://devfeed.tech/tags/llm.md>), [product](<https://devfeed.tech/tags/product.md>), [routing](<https://devfeed.tech/tags/routing.md>)

## AI overview

Grab describes Jarvis Pro, an AI assistant for account managers that routes a request to a constrained task type before generating an answer. The design aims to avoid confident but unsuitable merchant recommendations, and reports offline routing and answer-quality evaluation results.

## Source excerpt

Introduction The first Jarvis Pro prototype could produce answers that sounded right. That was the problem. One early answer looked polished: it named the merchant, summarized the week, and recommended pushing promotions before the next review. It was also wrong. The merchant's order volume was down, but the sharper issue was operational: more outlets were paused and fulfilment had slipped. Sending more demand into that setup would have made the merchant look worse. That failure changed how we judged the system. Fluent was not enough. Jarvis Pro is the AI assistant we built for Grab account managers. Its job is to help them turn account data into better merchant conversations: what changed, why it changed, and what to do next. They rarely ask clean dashboard questions. They ask: "I am meeting this merchant tomorrow. What should I tell them?" or "Which accounts in my portfolio need attention this week?" Those questions hide decisions: scope, access, business diagnosis, and metric definition. If the system gets those wrong, confidence becomes a liability. So the core design became: route first, answer later. In an internal offline evaluation (not a measure of production performance or business impact), routing matched the expected safe route for 99.4% of 351 realistic prompts drawn from labelled eval sets from the first half of 2026. In a focused portfolio and brand answer-quality suite, the average score moved from 78.5 to 91.0. These figures come from offline launch-readiness evaluation only; they are not business-impact proof. Why dashboards were easier A dashboard answers a bounded question: "Show net sales for merchant X last week." An account review question has to diagnose the work to be done: "This merchant softened this week. Should I push promos, ads, or operations fixes before the review?" If outlets were paused, more traffic can backfire. If average order value fell, the next action may be menu or bundle design. If a dashboard, warehouse table, and local s