Building your agents in-house or starting on a platform that already works.
Building AI agents in-house gives full control, but according to Gartner only 48% of AI projects reach production, and it takes 8 months. With Shimli the first agent is ready in under 10 minutes, with channels, CRM, security and models already solved, and your team can extend it through API and MCP.
Why choosing well matters
- 48%
- of AI projects make it into productionGartner · May 2024 ↗
- 8 months
- is the average time for an AI project to go from prototype to productionGartner · May 2024 ↗
- 67%
- of the time, buying from a specialized vendor works; internal builds succeed a third as oftenMIT NANDA, The GenAI Divide · 2025 ↗
What has to be built before the first customer
An agent that talks to customers isn't just a model with a prompt. It's everything around it, and that's what takes the most time.
In-house, your team solves
- Contract models, pick them and migrate when better ones come out
- The agent's orchestration, memory and tools
- Connect and maintain each customer channel
- An inbox and a CRM for the advisors
- Encryption, permissions, traceability and approvals
- Measure and evaluate what the agent answers
And then, maintaining all of it when something changes.
With Shimli, from day one
I need a collections agent on WhatsApp connected to our core, with human approval for exceptions.
- The agent is built by conversation, in under 10 minutes
- FusionAI picks and updates the models for you
- Eight channels, omnichannel inbox and CRM included
- Encryption, per-client isolation, roles, human approval and traceability
- REST API with an OpenAPI spec and MCP to extend it
Your technical team focuses on what's specific to your business.
The comparison, point by point
Building in-house makes sense in some cases. The table shows what's left on each side.
| Criterion | Build in-houseyour own development |  Shimliall-in-one platform |
|---|---|---|
| Time to production | 8 months on average from prototype to production, per Gartner | First agent in under 10 minutes |
| Team required | AI, development and security engineers | The operations team, without code |
| AI models | Contracts with each provider; pick, test and migrate | FusionAI picks them and adopts better ones without you changing anything |
| Channels and CRM | Integrated or built separately | Eight channels, official WhatsApp and omnichannel CRM included |
| Security and traceability | Designed and audited from scratch | Encryption, per-client isolation, roles, human approval and a record of every decision |
| Control and extension | Full over every piece | Limits and policies you set, plus REST API and MCP to extend |
| Cost | Team salaries, infrastructure and model usage | Monthly plan with every feature, plus AI usage |
All of the above is in the $139 monthly plan, with AI usage in blocks of $49 per 2,450 queries. No implementation cost. See pricing
When each one fits
It isn't a contest: they're tools for different problems.
Building in-house fits if…
- AI is the product you sell, not a tool for your operation.
- You have a dedicated team and budget to maintain it for years.
Shimli fits if…
- You need results in operations this quarter, not in eight months.
- You want your technical team focused on what's specific to your business.
- You need security and traceability ready for a risk committee.
Frequently asked questions
What people ask when comparing.
Create your first agent in under 10 minutes.
Describe what you need to the assistant and watch the agent work. Or we book 30 minutes and look at it on your operation.
