Carly AI vs Sai (Simular): API-Based EA vs Computer-Use Coworker (2026)
Carly is an AI-powered scheduling assistant that works over email and SMS. Unlike traditional booking links or calendar tools, Carly reads messy email threads she is cc'd on, understands context, and sends real invites that keep the conversation natural. You can forward Carly an email, send her a text, or send screenshots and images for her to process and add to your calendar. It's built for busy professionals who want a human-like assistant that just works, handling coordination and calendaring so you don't have to. ChatGPT could never be this useful.
Carly and Sai both get called “AI agents,” but they’re built on opposite architectures — and the architecture is the whole story. Sai, made by Simular (a San Francisco company that raised a $21.5M Series A led by Felicis in December 2025, with NVIDIA’s NVentures participating), is a “computer-use” coworker. It runs on a private cloud desktop and does work the way a person would: it reads the screen, moves a cursor, clicks, and types across whatever apps are open — no native integrations required, because it drives the real interface of each app. It can even run a terminal and write code.
Carly does the opposite. She’s an executive assistant you reach over email and SMS, and she connects to your tools through direct API integrations — Gmail, Outlook, Google Calendar, and 200+ apps via bring-your-own-API-key. Instead of piloting a screen, she calls the endpoints that already exist to triage your inbox, draft replies in your voice, schedule and reschedule meetings, keep a contacts/CRM record, manage tasks, and send daily briefings. Sai is a general agent that operates a computer. Carly is a specialist that runs your inbox and calendar.
Feature comparison
| Feature | Carly | Sai (Simular) |
|---|---|---|
| Reach it over email | ✅ | ❌ (you drive a cloud desktop / app) |
| Reach it over SMS / text | ✅ | ❌ |
| How it connects to apps | Direct API integrations (200+ via BYO-key) | Drives each app’s on-screen GUI — no native connectors |
| Gmail + Outlook + Google Calendar | ✅ native | Via logging into and clicking the real web apps |
| Meeting scheduling over email/text | ✅ | Via navigating a calendar UI |
| Runs your inbox/calendar unattended | ✅ (API calls) | Human-in-the-loop approval required for critical actions |
| Desktop apps with no API / legacy software | ❌ | ✅ (its core strength) |
| Runs code / terminal | ❌ | ✅ |
| Speed on a routine task | Seconds (one API call) | Minutes (screenshot → reason → click loop) |
| Always-on | ✅ | ✅ — but only on the $200/mo tier; the $20 machine sleeps when idle |
| Availability | Generally available, no invite code | Early access, invite-gated; macOS app in public beta (Apple Silicon only) |
| Pricing | Flat $35/month | Credit-metered: ~$20 (≈$20 of credits) / $200 always-on / $500 unlimited |
Sai’s pricing verified on sai.work as of July 2026: an early-access Starter at $20/month that includes roughly $20 of credits on a cloud desktop that sleeps when idle, a Premium Starter at $200/month for an always-on machine, and Pro at $500/month for unlimited credits. Credits are reloadable and consumed per task, so a heavy or long-running workload draws them down faster than light use.
Why the architecture decides it
Direct integrations are faster and cheaper than driving a screen — for work that has an API. Everyday email and calendar work already sits behind mature, stable APIs (Gmail, Outlook, Google/Microsoft Calendar). Carly calls them directly. Sai reaches the same tools by opening them on a cloud desktop and clicking through the UI. That gap is not small: in one published head-to-head benchmark, the computer-use approach used roughly 45× the tokens and took minutes where the API path finished in seconds, and an academic study of desktop agents found they take 2.7–4.3× more steps than necessary with end-to-end latency in the tens of minutes. For “find a time and send the invite,” clicking through a calendar is the expensive way to do a cheap thing.
Reliability is the trade-off computer-use makes, and vendors say so. A GUI agent can be knocked off course by a moved button, a login wall, or a CAPTCHA, and it can misread the screen and click the wrong thing. This isn’t a knock unique to Sai — it’s the category. Anthropic calls its own computer use “still experimental — at times cumbersome and error-prone” and warns not to use it “for tasks requiring perfect precision or sensitive user information without human oversight.” That’s exactly why Sai (sensibly) requires you to approve critical actions before it takes them — but a standing approval prompt is the opposite of a hands-off inbox. Carly’s API path is deterministic: the same scheduling request produces the same result without watching it work.
Sai genuinely wins where no API exists. This is the honest other side. If your task lives in a legacy desktop app, an internal tool, or a clunky web portal that never shipped an API, a computer-use agent is the right tool — it can operate anything a human can see, including running a terminal or filling out a bespoke form. Simular is a partner in Microsoft’s Windows 365 for Agents program and demos overnight, no-API workflows like extracting fields from scanned claim forms. That’s real, and Carly doesn’t do it. But it’s a different job than running your email and calendar.
Email- and text-native beats a workspace you visit. You forward Carly a thread, text her a request, or send her a screenshot of an event, and she acts — no app to open, no desktop session to launch, no prompt to compose. With Sai you’re operating (or supervising) a computer. For the daily back-and-forth of scheduling across time zones and clearing an inbox, being reachable where the work already arrives is a structural advantage.
Pricing rewards different usage. Sai meters credits, and the cheap-looking $20 entry tier includes only about $20 of credits on a machine that sleeps when idle — the genuinely always-on coworker is $200/month, and unlimited use is $500. Because every screen-driven step consumes tokens, a real always-on workload is where those credits go. Carly is a flat $35/month for an assistant that runs recurring email and scheduling admin without per-task metering. If your spend driver is “operate arbitrary software all day,” Sai’s model fits. If it’s “my inbox and calendar, handled,” Carly’s does.
What people actually say about Sai
Worth knowing before you buy: Sai has almost no independent review corpus yet. It has no reviewed profile on G2, Capterra, or Trustpilot, and much of the praise online traces back to Simular’s own comparison pages or a sponsored YouTube review. Its headline “72.6% on OSWorld, beating the 72.36% human baseline” benchmark is self-reported by Simular and rests on a best-of-ten-runs method with a ~0.24-point margin — a real result, but a self-announced and narrow one, not an independently verified rout. The most useful independent write-up (fazm.ai, March 2026) praises the full-desktop control and flags the honest cons: vision-based execution is slower than direct control, it’s Apple-Silicon-only for now, and usage cost accrues with heavy automation.
Which one fits you
Pick Sai if your pain is operating software that has no clean API — legacy desktop apps, internal tools, or long-tail web portals — and you want a general agent that can drive any interface, run a terminal, and work on a cloud machine overnight. Pick Carly if your pain is the recurring admin that eats your week: inbox triage, meeting scheduling over email and text, follow-ups, and CRM updates handled reliably and instantly through direct integrations, with no invite code and flat pricing. The two aren’t really competing for the same job — Sai automates a computer; Carly runs your calendar and inbox. If you’re weighing the broader field, see Simular (Sai) alternatives, the best AI executive assistants, and the best AI agents for productivity.
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"Before Carly, I relied on a Calendly link, but the whole process felt impersonal and not very professional. Carly changed that by handling all the back-and-forth, so I'm no longer stuck in endless email threads trying to line up schedules.
Now Carly reaches out to candidates, shares my real-time availability, lets them pick a slot, then sends a Zoom link and drops it straight into my calendar. She sends reminders to both of us before each call, which has significantly reduced no-shows and last-minute confusion.
On top of scheduling, Carly acts like a full executive assistant, sending me my schedule the night before so I can prepare for each call. It reminds me of the old x.ai assistant, but Carly is noticeably smarter, faster, and better suited to my healthcare recruitment business."
