Lab0
Lab0 provides AI agents that automate enterprise software implementation, compressing typical projects from roughly six months with nine people to about four weeks with three. The platform connects discovery, configuration, testing, and hypercare into a single implementation record, with agents that inspect systems directly, generate configuration rules, and validate workflows end-to-end.
- AI Agents
- Enterprise Software
- Artificial Intelligence
- Software Only
Funding
Raised to date
$500KRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Founder details are not available yet.
Product
Problem
Enterprise software implementation and system integration projects are typically done by hand by consultants over months, requiring weeks of interviews and document reading to discover requirements, manual configuration across systems with thousands of fields, and repeated testing cycles. The knowledge needed for implementation is scattered across kickoff calls, documents, specs, and people's heads, with no single person or document having the full answer, making projects slow, error-prone, and expensive.
Solution
Lab0 provides AI agents that streamline enterprise software implementation by connecting requirements, configuration, testing, and hypercare into a single implementation record. The platform's agents automate discovery by reading transcripts, documents, and specs, then asking targeted questions to fill gaps; inspect systems directly to find relevant fields and mappings; write configuration rules that translate statuses and values between systems; and validate entire workflows across roles, rules, and integrations. Lab0 compresses typical implementations from roughly six months with nine people to about four weeks with three people, enabling faster go-live timelines and improved delivery margins for its customers.
Target Audience
Primary customers are enterprise software companies seeking faster implementations and earlier go-live, and system integrators wanting to make their practices AI-native and improve delivery margins.
Features
- Automated discovery that turns scattered information from kickoff calls, requirements docs, integration specs, and stakeholders into one structured implementation blueprint
- Direct system inspection that finds the relevant fields (e.g., 14 relevant fields in ServiceNow out of ~4,000) across teams and maps them between systems
- Rule-based configuration generation that handles complex cross-system translation, such as writing conditional rules for Coupa-to-ServiceNow approval status mapping based on thresholds
- End-to-end testing that validates suites across roles, rules, and integrations, letting users follow one failure, apply the fix, and rerun only affected checks
- Automated hypercare that fills configuration from tickets, checks affected flows, and resolves tickets without manual intervention
- One connected implementation record linking requirements, stakeholders, decisions, configuration, integrations, migrations, test evidence, and release readiness from proposal through go-live