Startups

The Problem

As a startup, you know AI is table stakes. Your users expect it. Your investors ask about it. But building it properly is expensive.

• Hiring AI/ML talent is hard and burns runway fast

• Building orchestration, security, and analytics from scratch takes months

• You need to look credible to enterprise buyers, but you're a small team

• Shipping something half-baked damages trust with early customers

You need to punch above your weight without blowing your budget.

The Solution

strikeUp gives you the AI infrastructure that makes you look and act like a much bigger company.

• Sophisticated agentic architecture with orchestration, agents, and skills

• Enterprise-grade security and data privacy by default

• Gradual rollout with feature flags to de-risk launch

• User feedback tracking so you can iterate based on real usage

• We bake the latest AI technologies into your platform as they emerge

You get the AI capabilities of a world-class AI team. Without hiring one.

How It Works

1. Connect your product
   Import your API docs. strikeUp maps your product's capabilities and data.

2. Configure your AI
   Set up agents and skills. Define what the AI can do and how it behaves. No ML expertise required.

3. Roll out gradually
   Use feature flags to control who sees what. Start with internal testing, then expand to early customers.

4. Iterate on real feedback
   Track user feedback and AI activity. Improve based on what's actually happening, not what you assumed.

Key Capabilities

• Intelligent orchestration with agents and skills

• Feature flags for gradual, controlled rollout

• User feedback tracking built in

• AI model integrations managed for you (OpenAI, Anthropic, Google)

• PII masking and data privacy by default

• Enterprise-grade security without enterprise effort

• Analytics to prove traction to investors and customers

Example Outcome

Before:

You're six months into building AI. You've hired two contractors, burned through budget, and the prototype still isn't production-ready.

After:

You ship a working agentic layer in your product within two weeks. It's secure, it scales, and you’re operating as if you had your own dedicated team

Result:

Your customers are impressed. Growth accelerates, and you close your next funding round with AI as a key differentiator

Best For

• Seed to Series D startups building SaaS products

• Teams without dedicated AI/ML engineers

• Founders who need to ship fast and iterate

• Companies pitching to enterprise buyers who expect security and compliance