slug: aleph-alpha
provider: Aleph Alpha
generated_by: planning/capability-mapping/scripts/classify_capabilities.py
model: claude-opus-5
frame:
- Public Sector & Government
- Software & Technology
min_confidence: 0.7
capability_model:
  source: https://github.com/vincentmakes/turbo-ea-capabilities
  license: CC-BY-4.0
  attribution: Turbo EA Capabilities by Vincent Verdet — Turbo EA, https://github.com/vincentmakes/turbo-ea-capabilities,
    CC BY 4.0
  notice: NOTICE
edge_count: 10
edges:
- tag: tasks
  spec_file: aleph-alpha-tasks-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.75
  evidence: POST /complete  complete  Completion; POST /chat/completions  chatCompletions  Chat; POST
    /semantic_embed  semanticEmbed  Semantic Embeddings; POST /explain  explain  Explanation
  reason: These are LLM inference operations (completion, chat, embeddings, tokenisation, explainability)
    — the operational use of AI models. Closest candidate is Artificial Intelligence Management; no business-domain
    capability is realised by raw inference.
- tag: tokens
  spec_file: aleph-alpha-tokens-api-openapi.yml
  capability_id: BC-4270.40
  capability_id_l1: BC-4270
  capability_name: Developer Identity & Credential Management
  confidence: 0.75
  evidence: GET /users/me/tokens  Get issued API tokens; POST /users/me/tokens  Create a new API token;
    DELETE /users/me/tokens/{token_id}
  reason: Issuance and revocation of API tokens used to call the platform's public API — developer credential
    stewardship. Alternative reading is generic IAM, so confidence is moderate.
  recovered_from: sweep-20260829T005356Z-edges.json
- tag: v1/models
  spec_file: aleph-alpha-v1-models-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.75
  evidence: GET /v1/foundation-models    List all foundation models; POST /v1/models    Create a new model;
    v1.ModelDeploymentOutput, v1.GeneratorConfig
  reason: Registration, update, deletion and deployment of foundation models and inference runtimes is
    AI/ML model lifecycle management (MLOps).
- tag: Application Traces
  spec_file: aleph-alpha-application-traces-api-openapi.yml
  capability_id: BC-4220.20
  capability_id_l1: BC-4220
  capability_name: Observability Management
  confidence: 0.7
  evidence: POST /projects/{project_id}/traces_v2  Receive Otlp Traces; schemas TraceSpan, SpanStatus,
    TraceEvent
  reason: OTLP trace ingestion and retrieval for running applications is distributed-tracing observability.
    Mapped to Observability Management; moderate confidence since it is scoped to LLM application traces
    within a studio product.
- tag: Benchmark Executions
  spec_file: aleph-alpha-benchmark-executions-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.7
  evidence: POST /projects/{project_id}/evaluation/benchmarks/{benchmark_id}/executions  Create Benchmark
    Execution; "overview of all evaluation steps during execution (run, evaluation, aggregation)"
  reason: Executes evaluation runs of AI model/task outputs — part of the AI/ML model lifecycle (evaluation
    stage) in an LLM platform, fitting Artificial Intelligence Management.
- tag: Benchmarks
  spec_file: aleph-alpha-benchmarks-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.7
  evidence: '"A Benchmark provides a way to compare and evaluate the quality of your task results for
    a specific dataset"; schemas EvaluationLogic, AggregationLogic'
  reason: Definition and management of model evaluation benchmarks on an AI platform — AI/ML lifecycle
    (model evaluation) management.
- tag: Spans
  spec_file: aleph-alpha-spans-api-openapi.yml
  capability_id: BC-4220.20
  capability_id_l1: BC-4220
  capability_name: Observability Management
  confidence: 0.7
  evidence: '"A Span is a single unit of work within a Trace and represents an individual operation in
    the execution sequence" ... "providing detailed insights into each operation''s performance and behavior"'
  reason: Create/read spans within traces is distributed-tracing instrumentation, which maps to Observability
    Management (logs, metrics, traces). Slight ambiguity because these traces describe AI application
    runs rather than the SaaS platform itself.
- tag: Traces
  spec_file: aleph-alpha-traces-api-openapi.yml
  capability_id: BC-4220.20
  capability_id_l1: BC-4220
  capability_name: Observability Management
  confidence: 0.7
  evidence: A Trace provides a mechanism similar to OpenTelemetry for tracking the execution flow of a
    task ... Tracing is essential for performance monitoring and debugging.
  reason: Explicitly OpenTelemetry-style tracing for performance monitoring and debugging, which is observability
    management.
- tag: cluster
  spec_file: aleph-alpha-cluster-api-openapi.yml
  capability_id: BC-600.50
  capability_id_l1: BC-600
  capability_name: IT Infrastructure Management
  confidence: 0.7
  evidence: GET /cluster/gpus Get available GPU resources / GET /cluster/nodes List all cluster nodes
  reason: Compute cluster node and GPU resource inventory for the deployment platform, which is IT infrastructure
    (compute) management.
- tag: models
  spec_file: aleph-alpha-models-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.7
  evidence: Get All Model Cards / Get the tokenizer of a model / POST /models/chat/completions  Chat Completion
  reason: Catalogue of available LLM model cards plus inference endpoints (completion, chat completion)
    — management and serving of AI models, mapping to Artificial Intelligence Management. Part inference
    plumbing, so 0.7.
  recovered_from: sweep-20260829T005356Z-edges.json