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IDN Times is currently running a reader poll with a deceptively simple question: which kind of AI solution do you find most compelling? Readers get two options — AI for business and operations, or AI that serves a public need.
The poll grew out of Grab Ventures Velocity (GVV) Batch 9, Grab Indonesia’s accelerator for post-seed startups, which selected five AI companies from hundreds of applicants under the theme “Grab For Indonesia: Building an AI-Powered Resilient Ecosystem.”
Algobash is one of those five. And having spent the last several years building AI into hiring, we think the poll’s framing is worth arguing with — in a useful way.
The five companies, and what each one automates
| Startup | What it works on |
|---|---|
| Algobash | Recruitment and talent assessment |
| Dash | Frontline operations management |
| Fineksi | Risk scoring and credit decisions |
| Grivy | Connecting online customer interaction to offline sales |
| Sekilo | Halal protein supply chain systems |
All five receive mentorship, leadership training, and the chance to run a pilot project with Grab.
Why the business/society line breaks down
Sort that table and the split looks obvious. Credit scoring and frontline ops go in the “business” column. Halal supply chain goes in the “public need” column. Recruitment — well, recruitment is an HR function, so business, surely.
Except that every hiring decision has two parties, and only one of them is a company.
When a bank shortens its screening cycle from three weeks to four days, that is an operational win. But for the 2,000 applicants who were waiting, it is something else entirely: an answer instead of silence. When an assessment scores every candidate against the same rubric, the company gets consistency — and the candidate who did not go to a brand-name university gets a fair reading they would not otherwise have had.
In a country where youth unemployment remains stubborn and a single vacancy can draw thousands of applications, how companies screen is not only an internal process question. It is a question about who gets considered at all.
What “AI for operations” actually looks like in hiring
Stripped of the marketing, the operational case is narrow and concrete:
- Volume. Structured assessment lets a small team screen numbers that manual review cannot absorb.
- Consistency. The hundredth candidate is evaluated the same way as the first — which is not true of a tired human reviewer at 6pm.
- Evidence. A coding test or an on-the-job skill test shows what someone can do, rather than what their CV claims.
- Recruiter time. Hours moved out of administration and into the conversations that decide an offer.
And what “AI for people” looks like
The same system, read from the candidate’s side of the table:
- Equal conditions. Everyone sits the same assessment, with the same time and the same instructions.
- Faster answers. The most common complaint from Indonesian job seekers is not rejection — it is never hearing back at all.
- Less first-round bias. Skills-based screening reduces the weight of university name, photo, and address in the earliest cut.
- Reach. Remote assessment means a strong candidate in Makassar is not filtered out by geography before anyone reads their work.
None of this is automatic. Badly designed AI screening can entrench bias faster and at greater scale than any individual recruiter. That is an argument for designing it carefully and auditing it — not an argument that the technology sits neatly in the “business only” box.
What GVV Batch 9 signals for the ecosystem
The more interesting read of the cohort is that Indonesian AI has moved past the demo stage. These are companies embedding themselves in credit decisions, field operations, food supply, and hiring — the unglamorous infrastructure layer where a failure is expensive and a success compounds quietly.
That same shift is visible elsewhere: five Indonesian AI startups, Algobash among them, are pitching at Morning Pitch Asia: AI @Indonesia on 10 November 2026 to an audience of Japanese and regional investors.
So — which one is it?
Our honest answer is that the best AI solutions refuse the choice. They earn their place on a company’s balance sheet and make something measurably better for the people on the other side of the transaction. If a tool only does the first, it is a cost-cutting exercise. If it only does the second, it will not survive the next budget review.
You can cast your vote in the IDN Times poll here — it is still open.
And if you are thinking about where assessment fits into your own hiring process, our guide to choosing AI recruitment software and an ATS for 2027 is a practical place to start, or you can request a demo.