DownForAI

Refact.ai status: API, auth, latency & outage reports

Refact.ai is operational right now. DownForAI checks Refact.ai every ~75 minutes across 1 monitored surface, with 0 community reports in the last 24 hours.

Operational
Last probe 43 min ago·1 surface
Probe-monitoredLow confidence
📚 Docs →
100.0%
24h Uptime
391ms
p50 Network Latency
598ms
p95 Network Latency
0
Incidents (30d)

DownForAI monitors Refact.ai via a single endpoint — Refact AI Web. Current status: operational — all surfaces are responding normally. Measured uptime over the last 24 hours: 100.0%. Median response time (24 h): 391 ms; p95: 598 ms.

No incidents have been logged for Refact.ai, and no community reports were received in the last 24 hours. Probes run continuously across the configured surfaces.

Data confidence: LowLast checked 43 min ago · 1 monitored surface · 1 with 24 h latency data

Current Status

Operational
Everything works normally
Checked by our probes · 521ms
Verified 42m ago
No major incident reported
No reports in the last 24h

Having issues?

Help other users by reporting if Refact.ai is not working for you.

0reports in the last 24 hours

Surface Health

Refact AI WebOperational
HTTP 200p50 391ms42m ago

Uptime — last 24h

100.0%

Network latency — last 20 probes

Loading…

What DownForAI can verify about Refact.ai

No confirmed provider-side issue detected
DownForAI currently sees Refact.ai as operational based on available monitoring signals.
Signal source: public surface check · Monitoring confidence: Low
Still having trouble?

The issue may be account-specific, regional, network-related, or related to authentication, billing, quota, or rate limits.

Incident history (30d)

No incidents recorded in the past 30 days.

Reported symptoms

No user reports for Refact.ai in the last 24 hours.

Known error signatures

Common failure patterns and how to diagnose them

Provider details

Refact.ai is an open-source AI coding agent and assistant with a cloud plan and a self-hosted server option, delivered as IDE plugins. Cloud users depend on Refact's inference; self-hosters depend on their own GPU server.

Community channels
What we monitor
Refact cloud inferenceHosted completions and agent
IDE pluginsVS Code and JetBrains
Self-hosted serverUser-run inference
Operator notes
  • docs.refact.ai currently redirects to the project's GitHub wiki.

Fallback alternatives

What to use if this service is down

Refact cloud is down
Tabby or Continue (monitored on DownForAI) run open models locally; GitHub Copilot is the hosted fallback
Easy switch

How we monitor

DownForAI checks monitored AI service surfaces on a rotating schedule, roughly every 75 minutes per surface, from a single centralized probe infrastructure. For services with an official machine-readable status page, we use that official status signal when available. For other services, we perform a basic public-surface check. Some services block datacenter probes; in those cases we mark them as “Monitoring limited” instead of treating a failed probe as a confirmed outage. Status is classified as Operational, Degraded, or Outage. Network latency (check response time) measures how long the monitored endpoint took to respond to our probe — it is not model inference speed, time-to-first-token, or tokens-per-second performance. We are independent of all providers listed and receive no compensation to report any particular status.

Refact.ai statusEmbed this status badgeREADME · docs ▾
Markdown
[![Refact.ai status](https://downforai.com/api/badge/refact-ai.svg)](https://downforai.com/refact-ai)
HTML
<a href="https://downforai.com/refact-ai"><img src="https://downforai.com/api/badge/refact-ai.svg" alt="Refact.ai status" /></a>

Community Discussion

0/1000
No comments yet. Be the first to share your experience!

Still having issues with Refact.ai?

Let the community know and help others experiencing the same problem.