Multi-agent AI platform for accelerated ERP transformation and system integration
Tessera Labs builds a multi-agent AI platform designed to compress ERP transformations from years to weeks. The stack reveals a dual-layer architecture: enterprise system connectors (SAP, Oracle, Salesforce, Workday, NetSuite, ServiceNow) paired with modern data infrastructure (Kafka, PostgreSQL, Snowflake, MuleSoft). Heavy adoption of SAP S/4HANA and SAP Cloud APIs, plus active migration away from legacy SAP ECC and Dynamics 365, indicates Tessera positions itself as a modernization accelerator. The engineering-dominant hiring profile (26 of 39 roles) skewed toward senior and lead positions signals deep technical execution focus on agentic workflows and multi-system orchestration.
Tessera Labs operates a vendor-agnostic platform for enterprise ERP transformation, targeting mid-market and large organizations with complex, multi-system environments. The company claims to reduce transformation timelines by 90% and costs by 50% through intelligent automation of data harmonization, system integration, and workflow orchestration. The tech stack spans connectors to major ERP vendors (SAP, Oracle, Salesforce, Workday) and modern cloud infrastructure (AWS, GCP, Azure). Founded in 2024 and based in San Jose, Tessera currently employs 51–200 people, with active hiring concentrated in engineering, product, and data functions. The platform targets regulated industries and emphasizes security, governance, and avoiding vendor lock-in through adaptive intelligence.
Python, FastAPI, PostgreSQL, MySQL, Redis, Kafka, RabbitMQ, AWS, GCP, Azure. Integrates with SAP, Oracle, Salesforce, Workday, NetSuite, ServiceNow, MuleSoft, Snowflake. Currently adopting SAP S/4HANA, SAP Cloud APIs, and Kyma.
SAP (ECC, S/4HANA, FI, CO), Oracle (ERP, Fusion), Salesforce, Workday, NetSuite, ServiceNow, MuleSoft, and others. Actively migrating customers from SAP ECC to S/4HANA and away from Dynamics 365.
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Tessera Labs's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.