Kimp Reviews

1. June Xing

   · Marketing Director at Pro Marketing · about 4 years ago
   Great service, very happy!

   Kimp is great. Their entire process is very organized. Really love the experience from on-boarding to handling the tasks. Quality designs, fast turnaround. Highly recommended!

   🏁 Competitors: Design Pickle, Penji, ManyPixels, Graphics Zoo, Flocksy

   👍 Pros:    Very organized structure
2. Cathy Lee

   · Founder/CEO at Phenom Marketing · about 4 years ago
   Amazing service!!

   I really wish that I knew about this kind of service long ago. I was referred to Kimp by a friend so decided to give them a try. I have blown away by how much I was able to get done and free up my time. Great designs from the getgo. My project manager is very responsive and friendly to work with. Overall, I really enjoy working with the Kimp team and I can see this being a very long working relationship.

   👍 Pros:    Can outsource all my design requirement so i can focus on scaling my business|Great quality designs from the getgo, they nail most of the designs in the first attempt.|Very responsive and friendly project manager|Followups from management team|Very affordable|Fast turnarounds

   👎 Cons:    Nothing i can think of at the moment, they are really like part of my team

Temporal Reviews

Kimp mentions (0)

Temporal mentions (16)

• Your Agent Bills While It Waits. Here's the Fix.

  Durable execution — the pattern implemented by Temporal, Inngest, Rivet Actors, and now Cloudflare Workflows — treats waiting as a continuation rather than a loop:. - Source: dev.to / 4 days ago

• Compiler as Custodian

  Two specific moves stand out in Duncan's account. The first is durable execution, via Temporal — Mercury replaced fragile cron-and-database state machines with workflow code whose failure semantics are platform-handled (replay, retry, timeout, cancellation). Mercury open-sourced its hs-temporal-sdk, which wraps Temporal's official Rust Core SDK via FFI and provides a Haskell-native API. The dovetail with Haskell's... - Source: dev.to / about 1 month ago

• How we turned our workflow editor into a real SDK

  We picked Temporal as the first reference engine on purpose. Temporal has the strictest execution model we know of – a V8 sandbox, determinism constraints, replay-driven recovery. If our port contract holds up against that, easier engines – an in-memory test double, a BullMQ queue, or JSON-first platforms like Inngest or Restate – plug in through the same two interfaces. We're shipping Temporal first; the rest is... - Source: dev.to / about 2 months ago

• Three days debugging a missing trace

  The trick is to find whatever metadata channel the queue already gives you and use that and thankfully, almost every mature queue has one (probably because of this scenario). SQS has message attributes, Temporal has context propagators built into the SDK, and Hatchet (which we use to run our workflows) has a metadata field called additionalMetadata. - Source: dev.to / 3 months ago

• Best ChatGPT Alternatives in 2026: Evaluated on Automation, Persistence, and Data Ownership

  A typical production stack for teams using Claude or Gemini as the reasoning layer includes an LLM provider API, an orchestration layer (n8n, Temporal, or a custom Python service), application infrastructure (a server running the orchestration code), and a data layer (a database for storing results). Each boundary introduces a failure point. When the LLM provider changes its rate limits, as OpenAI did repeatedly... - Source: dev.to / 4 months ago