Rise2 AI
Rise2 AI is an AI and robotics lab that builds production-hardened agentic systems for enterprises, connecting autonomous agents to real tools like APIs, databases, and ticketing systems. The company also produces training data and benchmarks for embodied AI, and runs AI University programs to upskill product teams. Their deployment process includes a two-week workflow mapping phase and an eval suite built from client historical cases.
- Artificial Intelligence
- AI Agents
- Robotics
- Enterprise Software
- Software Only
- Education Technology
Funding
Founders
Founder details are not available yet.
Product
Problem
Most enterprise AI adoption stops at a chat box, leaving complex, multi-step workflows still dependent on human intervention between every action. Robots that could learn are blocked not by model architecture but by a shortage of quality training data and evaluation benchmarks that prove reliability before deployment.
Solution
Rise2 is an AI and robotics lab that builds, deploys, and teaches agentic systems that hold a goal across many steps in production environments. They design autonomous agents that connect to a company's real tools — APIs, databases, ticketing, and internal services — with scoped permissions and human approval gates for irreversible actions. The lab also produces training data and benchmarks for embodied AI, and runs intensive upskilling programs that turn product teams into builders. Their deployment process includes a two-week workflow mapping phase, building a working agent sandbox against real data, an eval suite built from the client's historical cases, and a handover with trained internal ownership.
Target Audience
Enterprises that need production-hardened autonomous agents for complex workflows, plus robotics teams requiring high-quality training data and benchmarks. The AI University serves product teams and organizations seeking to build in-house fluency with agentic systems.
Features
- Multi-agent systems with specialized agents and clear handoffs orchestrated toward a single objective
- Tool integration wired into enterprise APIs, databases, ticketing, and internal services
- Evaluation-before-deployment harness scored against historical customer cases with a measured accuracy bar
- Observability with full run traces showing what the agent saw, chose, and called
- Graceful escalation using confidence thresholds to route hard cases to humans, which then become evals
- Continuous learning loop where every run is scored and failures are captured for prompt and routing tuning
- Physical AI data and demonstration capture for embodied robots, paired with open research publication
- AI University programs for enterprise team upskilling in building and wielding agentic systems