--- title: "Cobrainer | Case studies | SurrealDB" description: "See how Cobrainer built a Rust-native agentic graph RAG and a graph-based memory agent on SurrealDB, getting graph, vector, and full-text from one engine without adding pgvector or OpenSearch." url: https://surrealdb.com/customer/cobrainer --- ![Building a skills-intelligence platform with Graph RAG and agent memory logo](https://surrealdb.com/assets/static/cobrainer-white.BkBOTd9l.svg) # Building a skills-intelligence platform with Graph RAG and agent memory Cobrainer's skills-intelligence platform runs a Rust-native agentic graph RAG and a graph-based memory agent on SurrealDB, getting graph, vector, and full-text from one engine instead of bolting on pgvector or OpenSearch. Industry HR technology Focus Agentic graph RAG & agent memory Location Munich, Germany 1. ![Babcock](https://surrealdb.com/assets/static/babcock.lo4rnVg1.svg) 2. ![ING](https://surrealdb.com/assets/static/ing.X3I6S3_V.svg) 3. ![British Airways](https://surrealdb.com/assets/static/british-airways.KEsZiwV-.svg) 4. ![Nvidia](https://surrealdb.com/assets/static/nvidia.DaIEuMil.svg) 5. ![Apple](https://surrealdb.com/assets/static/apple.D5pq4flY.svg) 6. ![SpaceX](https://surrealdb.com/assets/static/spacex.CQJEk-IL.svg) 7. ![Samsung](https://surrealdb.com/assets/static/samsung.CH-vQgnb.svg) 8. ![adidas](https://surrealdb.com/assets/static/adidas.DdTC5qhk.svg) 9. ![Tencent](https://surrealdb.com/assets/static/tencent.paQmLxyy.svg) 10. ![Alibaba](https://surrealdb.com/assets/static/alibaba.B16idgfM.svg) 11. ![PolyAI](https://surrealdb.com/assets/static/poly-ai.c3w_fAg6.svg) 12. ![Later](https://surrealdb.com/assets/static/later.Ds736jFO.svg) 13. ![Verizon](https://surrealdb.com/assets/static/verizon.BI7CajdX.svg) 14. ![Liberty Mutual](https://surrealdb.com/assets/static/liberty-mutual.B7qOU1pd.svg) 15. ![Walmart](https://surrealdb.com/assets/static/walmart.BjDg_Sr8.svg) 16. ![Carrier](https://surrealdb.com/assets/static/carrier.D21gC6NX.svg) 17. ![Saks Fifth Avenue](https://surrealdb.com/assets/static/saks-fifth-avenue.COIDpLSb.svg) 18. ![San Francisco Compute Company](https://surrealdb.com/assets/static/sfcc.B7jlImq4.svg) 19. ![Shield AI](https://surrealdb.com/assets/static/shield-ai.pINZ0KJr.svg) 20. ![Wix](https://surrealdb.com/assets/static/wix.DvHhmoBi.svg) COMPANY OVERVIEW ## Who they are Cobrainer, based in Munich, runs a skills-intelligence platform. As a startup that needed to move fast and iterate at pace, they wanted to improve agent accuracy and token efficiency without relying on a fragmented data stack and having to manage a variety of tools. Cobrainer required a flexible database that can handle many use cases with sufficient ergonomics, not only for engineers but also for the AI agents. 01 |KEY CHALLENGES ## What they needed to solve As Cobrainer looked to add agentic graph RAG and an AI agent with graph-based memory, it wanted these capabilities without fragmenting its stack and adding complexity, getting graph, vector, full-text, and flexible schema from one engine. ### Agent accuracy Flat vector retrieval surfaced only loosely related context. The team wanted graph structure so the agent could follow real relationships and ground its answers more reliably. ### Token efficiency Pulling broad vector matches into every prompt was wasteful, inflating the tokens spent on each agent call. ### Agent and graph RAG on one store An AI agent with graph-based memory living in the database, plus an agentic graph RAG that uses the relations between nodes the agent builds automatically. ### Pace of delivery New capabilities meant standing up new storage patterns quickly, without long migrations slowing the team's pace of innovation. 02 |SOLUTIONS ## How SurrealDB helped SurrealDB gave Cobrainer graph, vector, and full-text in one engine, backing the agentic graph RAG and the agent's graph-based memory directly. ### One engine for graph, vector, and full-text A single store, queried through SurrealQL, covers documents, graphs, vectors, and full-text, so the agentic case needed no pgvector or OpenSearch alongside Postgres. ### Rust-native agentic graph RAG Built natively on SurrealDB's Rust SDK, combining graph traversal and vector similarity in a single query, replacing the earlier S3-and-OpenSearch RAG. ### Graph-based agent memory SurrealDB stores the agent's memory and session checkpoints, with a multi-layered, graph-based memory model that was quick to implement. ### Managed cloud inside the EU SurrealDB Cloud lets a lean team run the engine as a managed service with EU-region residency, keeping HR data inside the required boundary. > As a startup, we didn't want to fragment our stack every time we add a capability. For our agentic graph RAG, the alternative was weighing Postgres with pgvector and search extensions against bolting on OpenSearch, instead we got graph, vector, and full-text from one engine. What surprised us was how quickly we stood up a multi-layered, graph-based memory model for our AI agent, with SurrealDB handling its memory and session checkpoints. And SurrealDB Cloud kept all of it inside our EU data boundary. *Daniel Alker* Senior Cloud Platform Engineer, Cobrainer 03 |RESULTS ## The impact Cobrainer replaced its simple S3-and-OpenSearch RAG with an agentic graph RAG and built an AI agent backed by SurrealDB, adding both without fragmenting its stack. A multi-layered, graph-based memory model was fast to implement, and grounding the agent in graph relationships rather than loose vector matches improved accuracy while cutting LLM token costs per call. Cobrainer now has a flexible platform for current and future use cases. 3 IN ONE ENGINE ### Graph, vector & full-text A Rust-native agentic graph RAG and a graph-based memory store for the agent, both on SurrealDB, instead of adding pgvector and OpenSearch to Postgres. ↑ ### More accurate agent responses Graph traversal grounds the agent's responses in real relationships rather than loose vector matches. ↓ ### Lower token cost per call Fetching only graph-relevant context, instead of broad vector matches, cuts tokens per call. 3 MONTHS ### Time to production From evaluation to a customer-facing production deployment. MORE CASE STUDIES ## See what other teams have shipped From knowledge graphs to AI assistants - how enterprise teams are building on SurrealDB. ![Samsung](https://surrealdb.com/assets/static/4c58b81e7b3c9466.C_Hv0eml.svg) DATABASE ### [Unlocking insights with knowledge graphs](https://surrealdb.com/customer/samsung) Samsung Ads uses SurrealDB to build dynamic, real-time knowledge graphs for smarter campaign execution - collapsing three legacy data stores into one. Read case study ![Verizon](https://surrealdb.com/assets/static/18b99996c689000f.B5PQ-nI9.svg) DATABASE ### [AI assistant empowering 10,000 technicians](https://surrealdb.com/customer/verizon) Verizon uses SurrealDB to power a generative AI assistant for 10,000 field technicians, delivering instant access to documentation, outage updates, and workflows. Read case study ![Tencent](https://surrealdb.com/assets/static/401d8346058682c8.DqM87mst.svg) DATABASE ### [Unified infrastructure monitoring](https://surrealdb.com/customer/tencent) Tencent consolidated nine backend tools into one real-time monitoring platform powered by SurrealDB's multi-model context graph. Read case study ![PolyAI](https://surrealdb.com/assets/static/c5fa07c66cd05131.BnC7wHcc.svg) DATABASE ### [High-performance customer service AI powered by RAG](https://surrealdb.com/customer/polyai) PolyAI connects SurrealDB to Agent Studio for low-latency, customer-controlled RAG across voice AI experiences. Read case study ![Saks Fifth Avenue](https://surrealdb.com/assets/static/saks-fifth-avenue-white.pDJ9HGmf.svg) DATABASE ### [AI-powered personalisation at massive scale](https://surrealdb.com/customer/saks) Saks Fifth Avenue uses SurrealDB's vector search and graph capabilities to deliver real-time, AI-powered personalisation across 5 million luxury customers and 45 million monthly product-recommendation queries. Read case study GET STARTED ## Start building with SurrealDB The unified data layer for AI. Unify data. Unlock intelligence. Scale anywhere. ![Samsung](https://surrealdb.com/assets/static/4c58b81e7b3c9466.C_Hv0eml.svg)![NVIDIA](https://surrealdb.com/assets/static/nvidia.DaIEuMil.svg)![Apple](https://surrealdb.com/assets/static/f7dc2519e0d212bc.Cn8MYAK7.svg)![Verizon](https://surrealdb.com/assets/static/18b99996c689000f.B5PQ-nI9.svg)![Tencent](https://surrealdb.com/assets/static/401d8346058682c8.DqM87mst.svg) SOC 2 Type 2 GDPR Cyber Essentials Plus ISO 27001 [Start for free](https://studio.surrealdb.com/current/instances/deploy) [Contact us](https://surrealdb.com/contact) ```json {"@context":"https://schema.org","@type":"Organization","name":"SurrealDB","url":"https://surrealdb.com","logo":"https://surrealdb.com/assets/static/logo.BG7_TG2b.svg","description":"SurrealDB is the unified data layer for AI. 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