Jamal Carter

Compared a few options

Evaluated this against two competitors. Where it wins: lead enrichment and qualification and enriches leads with contextual data. Where it lags: lead quality depends on source data accuracy. On balance the feature set — especially pipeline building workflows — justifies the 5 stars for our use case.

Years in this space

I've evaluated a lot of these over the years. What stands out here is competing AI agents per query — handled better than most — and citations attached to claims improve verifiability. Multi-agent responses can be slower than single-model chat is my one real gripe. Worth the time if this is your use case.

Solid for our team

We rolled this out across the team last quarter and shows relevant formulas alongside calculations. Formula references for each problem fits neatly into how we already work, and support for multiple physics topics removed a step we used to do by hand. but it has held up under daily use.

Does the job

Pretty happy overall. Support for 15+ ad networks just works and useful for scaling multi-channel campaigns. Pricing and feature depth may vary by channel can be annoying, but no dealbreakers — I'd recommend it to a friend without hesitating.

Solid for our team

We rolled this out across the team last quarter and lower learning curve than prompt-only tools. Region-specific inpainting fits neatly into how we already work, and works on existing photos and uploads removed a step we used to do by hand. Quality depends on brush precision, which is the main caveat, but it has held up under daily use.

Use it every day

Honestly didn't expect to like it this much. Multi-step AI workflow orchestration is exactly what I needed, and fast prototyping with quick time to production. I do wish visual approach may limit highly custom logic, but I reach for it almost every day now and it just clicks.