What is Hal9? Understanding Managed vs DIY AI Development

Most founders think they need to choose: build everything yourself or hire an expensive dev team. Hal9 offers something different.

By Javier Luraschi, Founder @ Hal9

We're a platform that helps startup founders launch AI-powered products in 30 days through a combination of managed onboarding and a self-service platform. Think of it as having a fractional co-founder who handles the hard parts while you stay in control.

The Problem with Traditional AI Development

Here's what usually happens when founders try to build AI products:

Full DIY: You use tools like Replit or Lovable to spin up a prototype. It looks great. Users can click around. But then you hit a wall—your backend isn't connected, your data isn't clean, and your AI logic doesn't actually work at scale. You've built a demo, not a product.

Full Build-Out: You hire a team of engineers or pay an agency $200K+ to build the "perfect" MVP with every feature you've imagined. Six months later, you launch... and discover users only care about 20% of what you built. You've spent too much time and money on the wrong things.

Both approaches fail for the same reason: you're either under-investing in the parts that matter (backend, infrastructure, AI integration) or over-investing in features nobody asked for.

How Hal9's Managed Approach Works

Hal9 splits AI development into two parts that work together:

Hal9 Onboarding (Managed Service)

This is where our team acts like your fractional co-founder. We handle:

  • Design and architecture decisions
  • Backend development and AI integration
  • Infrastructure setup and deployment
  • Ongoing maintenance and iteration

You get dedicated engineering hours each month (capped by your plan). We scope your MVP to the smallest version that delivers real value, then build it fast. Usually in 30 days.

Hal9 Platform (Self-Service Tools)

Once your product is live, you can use our platform to:

  • Deploy generative AI solutions on your own
  • Connect to any data source (databases, files, APIs)
  • Customize everything with Python and open-source libraries
  • Run secure, private deployments on any cloud

The platform is model-agnostic—it works with every major LLM (OpenAI, Anthropic, Google, etc.). You're not locked into any specific AI provider.

What This Actually Looks Like in Practice

Let's say you're a founder who wants to build an AI tool that helps sales teams generate personalized outreach emails.

Month 1 - Managed Onboarding:

  • Week 1: We scope your MVP together. Maybe it's just one AI workflow that takes a prospect's LinkedIn profile and writes three email variations.
  • Weeks 2-4: Our team builds the backend, connects your data sources, deploys the infrastructure, and gets it running with your first test users.

Month 2+ - Platform + Onboarding:

  • You use the Hal9 Platform to add new features yourself (like connecting to your CRM)
  • When you hit something complex (like adding a fine-tuned model), you use your onboarding hours for expert help
  • You iterate based on real user feedback, not assumptions

Starting price: $2K/month.

That includes both the managed service hours and platform access (compute, storage, LLM calls).

Why This Matters for AI Startups Specifically

AI products are different from traditional SaaS.

With SaaS, you can prototype in Figma, validate with mockups, then build once you have customers. But with AI, users can't visualize what "smart recommendations" or "automated insights" actually feel like until the AI is working.

You need a real, functioning AI product to validate your idea—not wireframes or a UI prototype. And that requires actual backend work, data pipelines, and model integration from day one.

The problem is most founders don't have $200K to spend before knowing if anyone wants their product. That's where Hal9's incremental approach makes sense: spend $2K to validate the core workflow, then scale up the investment as you learn what works.

Managed vs DIY: When Each Makes Sense

Use Hal9's Managed Service when:

  • You're a non-technical founder who needs expert guidance
  • You want to move fast without hiring a full team
  • You need someone to handle infrastructure, security, and deployment
  • You're not sure exactly what to build yet and want help scoping

Use Hal9's Platform (Self-Service) when:

  • You already have an AI product and want to expand features
  • You have technical skills but need better AI tooling
  • You want to prototype internally before committing to managed help
  • You're optimizing costs by handling routine updates yourself

Most of our customers use both. They lean on managed service to get past the hard parts, then use the platform for day-to-day iteration once the foundation is solid.

Common Questions About Hal9's Approach

Q: Is this just outsourcing my product development?

Not quite. Outsourcing usually means you hand off requirements and get a finished product months later. With Hal9, you're involved in every decision—we're working alongside you, not for you. Think fractional co-founder, not dev agency.

Q: What if I want to bring development in-house later?

You own everything. All code, all infrastructure, all AI configurations. Hal9 uses standard open-source tools (Python, Docker, popular ML libraries), so any engineer can take over. There's no proprietary lock-in.

Q: How is this different from using ChatGPT or Claude to build my product?

LLMs are amazing for prototyping and generating code snippets. But they can't set up your deployment pipeline, connect to production databases, handle security configs, or debug integration issues. Hal9 bridges that gap—we use AI tools ourselves, but we also bring the systems knowledge to make everything work in production.

Q: Can I just use the platform without managed service?

Yes! We have a free tier for basic use cases (chat with CSV files, simple data apps). If you want to connect live databases or deploy custom AI workflows, you'll need a paid plan. The managed onboarding service is optional—you can upgrade to it anytime.

Q: What happens if I run out of onboarding hours?

Hours reset monthly. If you consistently need more, you can upgrade to a higher plan. Or you can pause managed support and just use the platform until you hit something that needs expert help again. We're flexible.

Why We Built It This Way

Most AI platforms force you into one mode: either fully managed (expensive, slow) or fully self-service (you're on your own).

We built Hal9 because we kept seeing the same pattern with early-stage founders:

  • They'd spin up a prototype fast using no-code tools
  • They'd realize they needed real engineering to make it production-ready
  • They'd waste months trying to hire the right team or figure it out themselves
  • By the time they had something real, the market had moved on

Hal9 lets you skip that painful middle part. You get expert help when you need it, and independence when you don't. You move fast without overspending, and you learn as you build instead of spending six months in a vacuum.

The goal isn't to do everything for you—it's to get you from zero to validated product as quickly as possible, then give you the tools to keep iterating on your own.

If you're trying to launch an AI product and you're stuck choosing between DIY chaos or expensive overkill, Hal9 might be the middle path you're looking for.

Ready to build your AI product in 30 days?

Book a strategy call with Hal9's founder Javier or check out our plans to see what fits your needs.

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