LangSmith Agent Engineering Platform vs. Weights & Biases

In my personal experience I am using LangSmith Agent Engineering Platform in production-grade AI Systems, due to the feature of instant visual tracing of complex graph loops, API segmentations, tool calls and so much more without any boilerplate to be mentioned. Still the drawbacks are visible in development or research phases, where open-sources technologies to go well, or tasks which can be better achieved with single API call or static sequential chains.

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

No brainer to use it when doing ML experiments as it is very easy compared to any other open source tool. You don't have to host anything like in Tensorboard.

Experiment details can be shared very easily with public using the reports

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Debugging make simple by using Lang Smith.
• Easy to integrate.
• Cost Effective to use.

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Metrics Logging
• Hyperparmeters Sweeps
• Model Artifcats

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Mention different types of eval factors.
• Create more dynamic dashboards based on data.

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Dashboard lags when we log a lot of metrics
• Improved support for matplotlib charts and documentation of wandb custom charts is not straghtforward

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

In my opinion the technologies and concepts which I use with LangSmith Agent Engineering Platform like API tracing, prompt management, Prompt Hub and Agent Builder were like pioneer in the market with LangSmith Agent Engineering Platform. There are some scopes of improvements in terms of compatibilities and open-source tooling gaps but overall, it has to be on the list if you are doing AI-engineering at Production level.

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

Pretty generous with the Free-tier and best suited if you are using open-source technologies.

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Simple and Easy.

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Made it very easy to track experiments
• Track ML and Business Metrics improvements across experiments
• Reproduce runs which is essential in ML modelling

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info