The knowledge lives in people's heads
Leave policy for the Taiwan office, the warranty terms, which discount needs sign-off. An assistant taught on your handbook that quotes the clause and names the source is Glimmer's core promise.
Comparison
Olano vs Glimmer
The short verdict: both are Singapore-built, both are deployed for you rather than sold as a login, and both refuse the per-seat model - so the choice is not about which is more capable in the abstract. Glimmer is an internal AI teammate: it sits in the group chat your staff already open, is taught on your handbook and your data, and answers with the source shown. Olano is an operating layer for the work itself: persistent agents on your customer channels and internal systems, delegating to each other, acting under approval gates with an audit trail behind every action. Glimmer is built around the colleague's question. Olano answers the colleague's question too, and the customer's at 9.40pm - that is the line.
Side by side
The dimensions that decide the choice - not model benchmarks.
| Dimension | Glimmer | Olano |
|---|---|---|
| Who talks to it | Your own staff, in the shared team chat they already use - Slack, Telegram, Google Chat or Microsoft's own team chat. | Your staff and your customers. Agents run on WhatsApp, Telegram, email, Slack, SMS and 15+ messaging channels, plus inbound webhooks that fire on business events. |
| The core promise | An AI teammate that knows your business: taught on your handbook, policies and data, and it names the source of every answer. | A team of agents that does the work: answers enquiries, updates systems, runs scheduled jobs, and escalates what a human must decide. |
| Approvals & audit | Answers are sourced and checkable, and the deployment reports what was asked and answered. No published approval-gate model. | Trust levels 0-4, per-category approval gates (financial actions, external sends, and more), and an immutable audit trail on every action. |
| One agent or many | One shared assistant in the channel, in three modes Glints names Analyst, Operator and Builder. | An org chart of specialists that delegate to each other - 180+ specialist archetypes, 19 starter teams - with delegation itself gated and logged. |
| Building things | Non-engineers describe a tool in plain English and Glimmer builds it - a strength Glints demonstrates on its own product and website. | Not a code-generation product. Agents use 450+ connector tools, 75+ built-in integrations and 200+ MCP servers; custom APIs and MCP servers are built as part of a Studio engagement. |
| Models | Engine-swappable: Glints says the deployment is not tied to one AI company and can follow the best model. | Routes across 18+ providers - OpenAI, Anthropic, Google, DeepSeek among them - mixed per agent, with BYOK at no extra cost. |
| Deployment | One shared deployment, on your infrastructure or private infrastructure Glints sets up for you. | An isolated deployment per customer, hosted and managed; custom AWS/GCP regions available, or self-hosted on your own infrastructure. |
| How you buy it | Priced after a scoping call. Glints notes most builds may qualify for grants such as EDG, and offers a leadership workshop with seats from S$779. | Two doors: a Studio engagement scoped and quoted in SGD before any work begins, or Olano Cloud as a self-serve managed deployment from $25/month. |
Glimmer's column reflects what Glints publishes on its own product page, checked 3 September 2026. Where its page does not say, this table says so rather than guessing.
Where Glimmer fits
Glimmer is aimed squarely at a problem plenty of Singapore companies have: staff questions answered inside the team chat.
Your bottleneck is the analyst queue
"Why did revenue drop on this account?" answered from your own data in minutes, in the open, is the demo Glints leads with - and they run their own company on it.
Your team already lives in one chat
If everyone is in Slack or Teams all day and no customer ever messages you directly, an assistant in that room is what Glimmer is designed for.
You want the vendor to have eaten their own cooking
Glints built Glimmer to run Glints first and publishes the actual threads. That is a fair thing to weigh.
Where Olano is the better fit
The internal-assistant model stops at the edge of your company. Past that edge the requirements change: something is acting in front of a customer, under your name, and it has to be governed.
Customers message you, not just colleagues
Enquiries land on WhatsApp at 9.40pm and on Saturday. Olano agents answer on the channel the customer already uses - see WhatsApp AI customer service.
Something has to be approved before it goes out
Human-in-the-loop by design: outbound actions wait for approval by default, trust levels 0-4 decide what runs unassisted, and every action lands in an audit trail you can read afterwards.
The work spans several systems
One enquiry updates the CRM, checks live stock, and pencils a follow-up. Specialists delegate across 450+ connector tools rather than one assistant answering from documents.
Work should start without being asked
Scheduled tasks and event-driven monitoring: the twice-daily tender check, the low-stock reorder, the Monday pipeline report - running before anyone opens a chat window.
Where the two overlap
Both companies argue against buying everyone a separate AI subscription, and both are right: ten logins that know nothing about your business is ten people pasting the same background in by hand. Both keep the model layer swappable rather than betting the deployment on one AI vendor. And both will scope, build and deploy it for you rather than hand over a bare login, which is considerably more likely to still be running in month six.
The real difference is what the system is accountable for. Glimmer is accountable for an answer, and it makes that answer checkable - the source is shown, and it says when it cannot confirm something. Olano is accountable for an action taken on your behalf, so it carries the machinery an action needs: approval gates before anything leaves the building, trust levels, an audit trail, hard spend caps, and an isolated environment per customer. And because Olano agents also answer from your uploaded documents, the same deployment covers the internal questions as well.
FAQ
Can we run both?
Yes, and for some companies that is the sensible answer: an internal assistant for staff questions over your handbook and data, and Olano for the customer-facing and cross-system work that needs approvals and an audit trail. Olano composes with existing stacks through its 200+ MCP server library and inbound webhooks rather than demanding to be the only thing you run.
Does Olano work inside our team chat too?
Yes. Slack and Telegram are two of the 15+ channels Olano agents run on, and agents read your uploaded documents as a knowledge base, so the internal question-answering pattern is available. The difference is that the same agent team also works the customer channels and your operational systems, under the same approvals and audit trail.
Both of you are Singapore companies. Does that matter?
For some buyers, quite a lot: local support hours, an understanding of PDPA, and grant paperwork that is not an afterthought. Olano is a Singapore AI studio; see our Singapore grants reference for what PSG, EDG and the incoming EDGE scheme actually fund, and our PDPA guide for the data questions worth asking any vendor - including us.
How do the prices compare?
Neither is a per-seat subscription, and neither publishes a single number, because both are scoped to the build. Glints prices Glimmer after a scoping call and points at grants such as EDG. Olano quotes a fixed proposal in Singapore dollars before any work begins, with hard AI spending controls agreed in advance - and, unlike a pure studio model, also offers Olano Cloud as a self-serve managed deployment from $25/month if you would rather start without a project.
How was this comparison researched?
Everything in Glimmer's column comes from the product page Glints publishes at ai.glints.com/glimmer, read on 3 September 2026. Where that page does not address something - approval gates, for instance - the table says so rather than assuming the answer. Product pages change; if you are reading this months later, check theirs, and tell us if we have gone stale.
Related reading
Other comparisons, and the patterns behind them.
Olano vs Lindy
A self-serve credit-metered agent builder, compared with a managed deployment.
Olano vs Botpress
The developer-first build-it-yourself platform, compared side by side.
WhatsApp AI customer service
The customer-facing pattern an internal assistant does not cover.
How to choose an AI agent platform
The checklist to take into any vendor call - ours included.
Singapore grants for AI projects
PSG, EDG and the incoming EDGE scheme - caps, timelines and what must be true first.
Checked 3 September 2026 against the vendor's own published material: Glimmer product page, Glints. Comparisons go out of date - if we have described your product wrongly, write to support@olano.ai and we will correct this page.
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