Lamatic 2.0 - IDE to build & deploy AI agents on serverless

@fmerian  @amanintech  Love the focus on speed, debugging, and serverless edge deployment. Congrats on the launch

@fmerian  @amanintech  - Congrats on the launch! Very cool product. Have you considered integrating Connect into Lamatic? It would be amazing to have 2500+ additional apps in your agent builder. DM me if interested and I can connect you with the team.

@tod_sacerdoti thanks a lot. We would love to explore the are of integrations. Sending you a DM.

Thanks @dineshan_sithamparanathan 

@fmerian  @amanintech Lamatic 2.0 looks super promising! Love the visual flow builder and seamless deployment. 🚀

@raza_noorani Thank you so much for your kind words and for sharing your experience with Lamatic! It's incredibly rewarding to hear how our middleware layer has helped streamline your LLM orchestration processes.

We love working with Impero IT @raza_noorani. You guys rock! Thanks for your early trust in Lamatic!

Thanks @alexwestco Most common use cases are RAG pipelines, Chatbots, and Search pipelines. You can explore detailed guides for specific implementations at lamatic.ai/guides, which includes tutorials for beginners and intermediate users on building everything from basic chatbots to complex RAG systems with various integrations.

Thanks for asking @alexwestco ... most every product person I've met knows how AI could improve their product (many have a list of these things parked on their roadmap). Once they describe this in the form of a JSON payload, the job is 90% done. Lamatic makes it fast & easy to engineer a custom AI-powered API that delivers that exact result reliably. But that doesn't answer your question does it ;-)

The most common use case (which can be done in <1 hour for free on Lamatic) is to vectorize a product's /Docs/ folder and deploy a Lamatic chatbot that answers customers' actual questions (rather than forcing them to hunt for the answer). The added benefits to the Product Team are (a) they can see exactly what people are asking AND (b) they can intervene if the answer their documentation gives is sub-optimal (by improving their /Docs/ and, if it's an important enough error, contacting the customer with the right answer). In the same way, you can very quickly make your Release Notes useful. While these are fast, simple, and nearly universal ... the power of Lamatic is the ability to build any agent you can imagine.

Hope that helps Alex!

Chuck

@cranqnow Thank you for your enthusiastic feedback!

Our goal at Lamatic.ai is to make building and launching AI agents as straightforward and efficient as possible for developers. We offer a free Starter plan that includes essential features for building, testing, and validating your GenAI ideas, we also provide Pro and Enterprise plans with additional capabilities for scaling applications in production

Thanks for your comment Sam@cranqnow! Middleware is a "must-have" like you said for anyone building production-grade AI. You can do it custom DIY or use Lamatic. Lamatic is already a better, faster and cheaper option. Our 2 goals now are to extend this ... and to make sure the world knows about Lamatic. Thanks for helping us get the word out Sam!

@kay_arkain It’s the perfect solution for startups and enterprises to Build Performant, Reliable AI Agents at Scale!

Great question @kay_arkain! I'll add to Vrij's comment and say that Software Development Agencies are also finding huge value from Lamatic (see Raza's comment above). It helps them deliver agentic apps faster, cheaper, more predictably and more profitably.

@jonurbonas Lamatic handles team collaboration through an organization-based structure. Organizations can contain multiple projects, and team members can be added with specific roles. All members within an organization can access its projects.

Great question @jonurbonas! You clearly have experienced the slow, error-prone nature of agent building without a collaborative studio like Lamatic (where everyone is working in their own environment and pushing stuff to a Dev whose job it is to put it in a Sandbox only to repeat that process over-and-over again until the agent is "production-ready".

As Arun described, Lamatic eliminates this and accelerates the ongoing process of iterating agents (as models, requirements, and techniques change) by an order of magnitude. 

@pablo_velez  Thank you!

So happy to hear that.

Thank you for your feedback @pablo_velez and for your question. New in version 2.0 is our Prompt Management function that does (I think) exactly what you're describing. That said, we'll be very interested in your feedback on whether it checks all your boxes. Please share your feedback on product.lamatic.ai (where everyone else can see & upvote it).

@mihajlo_kuzmanoski Thank you very much, Mihajlo!

Appreciate the feedback @mihajlo_kuzmanoski ... one thing is for sure, we need to keep evolving as fast as this market is. We can't just rely on our own thinking to do this - we need smart people like you to lean in as we build in public: https://product.lamatic.ai/

@adam_rubenstein Thank you, Adam!

@dhruv_pamneja Indeed

@shenjun Thank you for your feedback

And Lamatic is a HUGE fan of Navigamo @bgiffuni! Thanks Blas for you and your team's ongoing support. 

@bgiffuni thanks for your trust and its been an absolute delight to work with you.

Thanks for the feedback and the instightful questions @yuliya_fomina! We love that you see Lamatic as an end-to-end solution. It is for this reason that we think of Lamatic as more than a framework. It's managed middleware combined with an IDE & SDK which is built specifically for product teams working to move faster than their (current & potential) competitors.

To answer your specific questions:
1) Memory Management: The Lamatic platform provides its own memory. Not only does this extend the context window of whatever foundation models you connect your Lamatic flows to, it also allows you to maintain context across models and user sessions.
2) GraphQL API: Unconstrained flexibility is exactly the reason Lamatic leverages GraphQL to serve out whatever agents / APIs you build. The moment you update the input (or output) schema and deploy, your API and all the API Docs are updated instantly in production. It is literally 100% customizable.

@german_merlo1  Thank you very much Germán Merlo