Gradient Labs

We are building an autonomous AI agent aiming to resolve up to 80% of customer queries (incl. using actions and account data), enabling companies to scale CX with minimal human staff. The product caters to companies that aim to offer exceptional customer support and want a guarantee of good customer outcomes rather than a "best effort" automation.

http://www.gradient-labs.ai

2-10 employees

Growth Trajectory

The company plans to expand beyond customer support to automate back-office procedures and fraud/financial crime alert management. They are targeting companies with complex support needs and regulated industries, aiming for superhuman quality support through continuous AI agent improvement. Their focus on AI agents' ability to understand intent and handle complex scenarios suggests further expansion into other industries and use cases.

Technical Challenges

Integrating with complex and varied customer systems.

Automating non-linear customer support processes.

Ensuring data security and compliance (GDPR, SOC 2).

Managing the non-deterministic nature of LLMs.

Extracting value from historical conversations without extracting wrong or irrelevant information.

Building AI agents that understand intent, handle technically inaccurate statements, leverage implicit knowledge, and deal with complex scenarios.

Encoding human instincts as explicit tasks for LLMs

Tech Stack

AIPlain Language ProcessingLLMs (Large Language Models)Public APITemporal WorkflowsActivitiesState MachinesVector StoresRAG (Retrieval Augmented Generation)Python

Team Size

Engineers

Product Managers

Customer Support Team

AI/ML Researchers

Key Risks

Convincing companies with existing chatbot solutions to switch to their AI agent platform.

Ensuring the AI agent's performance consistently matches or exceeds human agent quality, especially in handling nuanced or ambiguous customer intents.

Integrating with complex and varied customer systems while maintaining data security and compliance (GDPR, SOC 2).

Reliance on LLMs can introduce non-deterministic behavior, requiring robust guardrails and consistency checks.

Incomplete or outdated company knowledge bases may hinder AI agent performance and require significant data curation efforts.

Opportunities

Expanding AI agent capabilities to automate back-office procedures and other operational tasks beyond customer support.

Targeting regulated industries (banking, insurance) where governance and compliance are critical, leveraging their AI agent's built-in governance features.

Developing new skills and chains for AI agents to handle a wider range of tasks, enhancing their value proposition.

Leveraging partnerships with existing support platforms (Intercom, Zendesk, Freshdesk) to accelerate market penetration.

Improving AI agents' ability to understand customer intent, handle inaccurate statements, and leverage implicit knowledge to provide more effective support.

Live Data Stream

Access Our Live VC Funding Database

30,000+ funded startups

tracked in the last 3 months

B2B verified emails

of key decision makers

Growth metrics

Real-time company performance data

Live updates

of new VC funding rounds

Advanced filters

for sophisticated queries

API access

with multiple export formats

Access Database

Updated every 5 minutes