Seldon vs Zep

Only Seldon

• Seldon Core 2 declares models and pipelines as Kubernetes custom resources
• Automatic inference server selection, scaling, monitoring and audit logging from one manifest
• Composable data-centric pipelines connecting models, processing steps, custom logic and monitors over Kafka
• MLServer lightweight multi-framework inference server with REST and gRPC support
• Open Inference Protocol compatibility across model types
• A/B tests, canary deployments, shadow deployments and multi-armed bandits for production routing
• Multi-model serving with LRU memory swapping and overcommit to provision more models than hardware allows
• Real-time observability with every prediction logged and auditable via Prometheus, Grafana and custom dashboards

Only Zep

• Temporal context graphs that record facts with a validity window
• Fact invalidation when new information contradicts the graph, with old facts kept as history
• Point-in-time queries: ask what is true now or what was true on a past date
• Multi-source ingest from chat history, business data (JSON) and user interactions
• Automated context assembly returning token-efficient context blocks
• Observations: patterns, recurrences and co-occurrences detected across the graph
• Provenance on every fact, traced back to the source episode
• Context Lake architecture governing millions of context graphs as one system

Only Seldon

• Serving real-time ML inference inside a regulated bank's own Kubernetes cluster
• Running drift and outlier detection alongside live predictions in pharmaceutical model pipelines
• Promoting a challenger model through canary or shadow deployment without downtime
• Consolidating many small models onto shared inference servers to reduce GPU spend
• Adding explainability to every prediction for audit and compliance review
• Deploying generative AI workflows with prompt orchestration and guardrails on existing Kubernetes infrastructure
• Standardizing model handoff between data science teams and platform engineering
• Keeping inference and data on-premise where cloud egress is not permitted

Only Zep

• Giving a production customer-support agent persistent memory of a user's prior issues and stated preferences
• Fusing CRM, billing and product-event JSON into a single per-user graph an agent can query
• Answering point-in-time questions such as what a customer's plan or preference was on a specific date
• Reducing prompt token spend by replacing full chat transcripts with an assembled context block
• Auditing why an agent said something by tracing the underlying fact back to its source episode
• Detecting behavioural patterns, such as repeat upgrade timing, and feeding them to an agent as Observations
• Running agent memory inside a regulated customer's own VPC via Bring Your Own Cloud
• Exposing agent memory to IDEs and assistants through the Memory MCP Server

Only Seldon

• Prometheus
• Grafana
• Kafka
• Jaeger
• Elasticsearch
• Triton Inference Server
• MLflow
• Weights & Biases

Only Zep

Nothing exclusive in this list.

Seldon

• Open Source (Seldon Core 2, MLServer, Alibi Detect, Alibi Explain) $0/mo or $0/yr

  Seldon Core 2 Kubernetes-native MLOps and LLMOps deployment engine · MLServer multi-framework inference server with REST, gRPC and Open Inference Protocol · Alibi Detect for outlier, adversarial and drift detection · Alibi Explain for local, global, black-box and white-box explanation methods · Self-hosted on your own Kubernetes cluster

• LLM Module Custom quote

  Gen AI workflow deployment with prompt orchestration · Built-in and configurable guardrails for LLM deployment · Observability and production-ready scaling for generative workloads · Priced through a scheduled platform briefing; no public figure published

• MPM Module Custom quote

  Model Performance Metrics for classification and regression models · Real-time quality insights on production models · Detection of performance degradation before business impact · Priced through a scheduled platform briefing; no public figure published

• Enterprise Platform Custom quote

  Oversight and governance for ML and LLM deployments at scale · Enhanced authentication and team controls · Audit trails for regulated industries · Priced through a scheduled platform briefing; no public figure published

Zep

• Free $0/mo or $0/yr

  10,000 credits per month (no rollover or auto top-up) · 2 projects · Memory MCP Server seat · Custom entity/edge types · Variable rate limits depending on service-wide load · Lower priority Episode processing · Community support

• Flex $125/mo or $1250/yr

  50,000 credits per month included, then $25 per 10,000 credits · Auto top-up at 20% (10,000 credits / $25) · 30-day credit rollover · 600 requests per minute · 5 projects · 5 Memory MCP Server seats · 10 custom entity/edge types · API logs retained 1 day · Unlimited memories and retrieval users · Community support · Cloud deployment

• Flex Plus $375/mo or $3750/yr

  200,000 credits per month included, then $75 per 40,000 credits · Auto top-up at 20% (40,000 credits / $75) · 60-day credit rollover · 1,000 requests per minute · 10 projects · 15 Memory MCP Server seats · 20 custom entity/edge types · Observations, custom extraction instructions, webhooks, analytics · API logs retained 7 days · Unlimited memories and retrieval users · Priority support