# Dataset Injection API

*/Software/Dataset_Injection_API*

## Solution Overview

The Dataset Injection API programmatically updates live retrieval-augmented generation (RAG) systems with new information. It accepts raw JSON, CSV, or unstructured PDF text via REST endpoints, automatically chunks the data, generates vector embeddings, and writes directly to target vector databases like Pinecone or Weaviate. The outcome is an instantly updated knowledge base for downstream applications, eliminating the need for manual data uploads or batch-process retraining.

MLOps engineers and backend developers integrate this API to solve data staleness in dynamic environments like e-commerce or live customer support. Instead of building custom ingestion pipelines every time a product catalog changes or a new compliance manual is released, development teams point their webhooks at the API. It removes the engineering overhead of managing chunking strategies, embedding rate limits, and database synchronization.

Operating as a headless SaaS primitive, the API consumes raw storage buckets and third-party embedding models below it, while exposing clean endpoints for autonomous agents and conversational interfaces above it. It includes a programmable quarantine threshold that flags malformed schemas or out-of-bounds token counts, holding anomalous data payloads for human review before they are injected into production vector stores.

## Headless Saas Data Model

**Entities**:
- Name: DataPayload · Description: Incoming raw data request representing a file or payload for vector injection
- Name: Workspace · Description: Tenant isolating configuration, credentials, and injection history
- Name: VectorStore · Description: Target vector database configuration such as Pinecone or Weaviate credentials
- Name: DocumentChunk · Description: Segmented blocks of text generated from a payload for vector embedding
- Name: QuarantineRule · Description: Configurable threshold for flagging malformed schemas or excessive token counts
- Name: QuarantineFlag · Description: Anomalous data record held for human review before vector injection
**Relations**:
- To: DataPayload · From: Workspace · Label: owns payloads · Cardinality: one-to-many
- To: VectorStore · From: Workspace · Label: configures stores · Cardinality: one-to-many
- To: QuarantineRule · From: Workspace · Label: defines rules · Cardinality: one-to-many
- To: DataPayload · From: VectorStore · Label: receives injections from · Cardinality: one-to-many
- To: DocumentChunk · From: DataPayload · Label: splits into · Cardinality: one-to-many
- To: QuarantineFlag · From: DataPayload · Label: triggers · Cardinality: one-to-many
- To: QuarantineFlag · From: QuarantineRule · Label: generates · Cardinality: one-to-many
**Tenant Anchor**: Workspace
**Primary Resource**: DataPayload

## Api Definition

**Protocols**:
- REST
- SDK
- MCP
- Webhooks
**Consumed By**:
- [Knowledge Base Agent](/Agents/Knowledge_Base_Agent)
- [Catalog Sync Agent](/Agents/Catalog_Sync_Agent)
- [Support Triage Agent](/Agents/Support_Triage_Agent)
- [Compliance Review Agent](/Agents/Compliance_Review_Agent)
**Integrations**:
- [Pinecone](/Products/Pinecone)
- [Weaviate](/Products/Weaviate)
- [Amazon S3](/Products/Amazon_S3)
- [OpenAI](/Products/OpenAI)
- [Cohere](/Products/Cohere)
**Consumption Model**: An autonomous agent registers the MCP server to push raw files directly to the DataPayload endpoint, while backend systems POST updates via REST and monitor webhooks for injection status or quarantine events.
**Workflow Wrappers**:
- Name: Inject Data Payload · Wraps: accepts raw files, segments document chunks, executes embedding models, and commits vectors to the target store
- Name: Resolve Quarantine Anomaly · Wraps: updates the review status of a quarantine flag and automatically resumes the suspended payload injection process
- Name: Provision Vector Store · Wraps: registers a target database connection, validates embedding model credentials, and binds active workspace quarantine rules

## Api Function Cascade

**Ai Role**: AI embedding models transform document chunks into vector representations entirely straight-through, nested within a deterministic ingestion and storage pipeline that pauses only for external review when quarantine anomalies trigger.
**Cascade**:
- Kind: Code · Note: Receives payloads via REST, MCP, or fetches directly from Amazon S3. · Step: Ingest Raw Payload · Verb: ingest · Realizes: Ingest Source Data · Oversight: none
- Kind: Code · Note: Divides raw files into semantically scoped structural chunks. · Step: Segment Document Chunks · Verb: parse · Realizes: Parse Document Text · Oversight: none
- Kind: Generative · Note: Executes embedding models via OpenAI or Cohere integrations. · Step: Generate Vector Embeddings · Verb: transform · Realizes: Transform Data Formats · Oversight: none
- Kind: Code · Note: Suspends anomalous payloads pending consumer workflow review via webhook. · Step: Apply Quarantine Rules · Verb: validate · Realizes: Validate Data Quality · Oversight: review-on-exception
- Kind: Code · Note: Upserts processed vectors into Pinecone or Weaviate. · Step: Commit To Target Store · Verb: load · Realizes: Load Database Records · Oversight: none
**Optimizes**:
- [Injection Latency](/Metrics/Injection_Latency)
- [Successful Payload Injection Rate](/Metrics/Successful_Payload_Injection_Rate)
- [Data Pipeline Throughput](/Metrics/Data_Pipeline_Throughput)
- [Embedding Relevancy Score](/Metrics/Embedding_Relevancy_Score)

## Headless Saas Representative Offer

**Warranty**: Maintains a 99.9% API uptime SLA for the ingestion endpoint, providing standard service credits if availability drops below the threshold.
**Price Band**: Roughly $0.01 to $0.08 per megabyte of data processed and vectorized, depending on the selected embedding model and storage target
**Pricing Kind**: UsageMeter
**Deliverables**:
- API and MCP server access credentials
- Automated document chunking and embedding pipeline capacity
- Direct commit synchronization to target vector databases
- Quarantine queue routing and webhook event notifications
**Delivery Mode**: Instant self-serve provisioning where autonomous agents or developers authenticate via API key or MCP and immediately begin streaming raw payloads for ingestion.
**Business Function**: ProvideService
**Agent Checkout Support**:
- agentic-commerce-protocol
- stored-credential

## Headless Saas Crud Surface

**Auth Model**: API Key
**Endpoints**:
- GET /data-payloads — list data payloads across configured stores
- GET /data-payloads/{id} — fetch metadata and processing status for a single data payload
- POST /data-payloads — ingest a raw data payload for vector injection
- PATCH /data-payloads/{id} — update metadata or source format for an existing payload
- GET /workspaces — list workspaces representing tenant configurations
- GET /workspaces/{id} — fetch details for a specific workspace
- POST /workspaces — create a new workspace to isolate credentials and history
- PATCH /workspaces/{id} — update workspace name or configuration properties
- GET /workspaces/{workspaceId}/vector-stores — list target vector database configurations for a workspace
- POST /workspaces/{workspaceId}/vector-stores — configure a new vector store destination
- GET /vector-stores/{id} — fetch configuration for a specific vector store
- PATCH /vector-stores/{id} — update vector database credentials or index configuration
- GET /data-payloads/{dataPayloadId}/document-chunks — list segmented chunks generated from a data payload
- POST /data-payloads/{dataPayloadId}/document-chunks — append pre-segmented document chunks to a payload
- GET /document-chunks/{id} — fetch text content and token count for a specific document chunk
- PATCH /document-chunks/{id} — update chunk content or injection status
- GET /workspaces/{workspaceId}/quarantine-rules — list rules configured to trap anomalies
- POST /workspaces/{workspaceId}/quarantine-rules — define a new quarantine threshold or schema rule
- GET /quarantine-rules/{id} — fetch configuration for a specific quarantine rule
- PATCH /quarantine-rules/{id} — toggle rule activity or adjust token thresholds
- GET /data-payloads/{dataPayloadId}/quarantine-flags — list anomaly flags triggered by a payload
- POST /data-payloads/{dataPayloadId}/quarantine-flags — manually flag a payload record for human review
- GET /quarantine-flags/{id} — fetch details and anomaly reason for a specific flag
- PATCH /quarantine-flags/{id} — update the review status of an anomalous record
- POST /quarantine-flags/{id}/resolve — resolve the flag and release the payload for vector injection
**Multitenancy**: Row-level isolation
**Webhook Events**:
- data_payload.processed
- document_chunk.injected
- quarantine_flag.triggered
- quarantine_flag.resolved

## Headless Saas Erd

```mermaid
erDiagram
  Workspace {
    UUID id PK "tenant key"
    VARCHAR name
    TIMESTAMP createdAt
  }
  DataPayload {
    UUID id PK
    UUID workspaceId FK
    UUID vectorStoreId FK
    VARCHAR sourceFormat
    VARCHAR processingStatus
    DECIMAL totalTokenCount
  }
  VectorStore {
    UUID id PK
    UUID workspaceId FK
    VARCHAR provider
    VARCHAR indexName
    VARCHAR embeddingModel
  }
  DocumentChunk {
    UUID id PK
    UUID dataPayloadId FK
    TEXT textContent
    DECIMAL chunkTokenCount
    VARCHAR injectionStatus
  }
  QuarantineRule {
    UUID id PK
    UUID workspaceId FK
    DECIMAL maxTokenLimit
    BOOLEAN enforceSchema
    BOOLEAN isActive
  }
  QuarantineFlag {
    UUID id PK
    UUID dataPayloadId FK
    UUID ruleId FK
    VARCHAR anomalyReason
    VARCHAR reviewStatus
  }

  Workspace ||--o{ DataPayload : "owns payloads"
  Workspace ||--o{ VectorStore : "configures stores"
  Workspace ||--o{ QuarantineRule : "defines rules"
  VectorStore ||--o{ DataPayload : "receives injections from"
  DataPayload ||--o{ DocumentChunk : "splits into"
  DataPayload ||--o{ QuarantineFlag : "triggers"
  QuarantineRule ||--o{ QuarantineFlag : "generates"
```

## Neighborhood

### Composed into

- [Blazalidate](/Startups/Blazalidate) — composes · Startups

### Optimizes

- [Embedding Relevancy Score](/Metrics/Embedding_Relevancy_Score) — optimizes · Metrics
- [Injection Latency](/Metrics/Injection_Latency) — optimizes · Metrics
- [Successful Payload Injection Rate](/Metrics/Successful_Payload_Injection_Rate) — optimizes · Metrics
- [Data Pipeline Throughput](/Metrics/Data_Pipeline_Throughput) — optimizes · Metrics

### What it uses

- [OpenAI](/Products/OpenAI) — uses · Products
- [Weaviate](/Products/Weaviate) — uses · Products
- [Amazon S3](/Software/Amazon_S3) — uses · Software
- [Cohere](/Software/Cohere) — uses · Software
- [Pinecone](/Software/Pinecone) — uses · Software

### Who consumes this

- [Catalog Sync Agent](/Agents/Catalog_Sync_Agent) — consumed by · Agents
- [Compliance Review Agent](/Agents/Compliance_Review_Agent) — consumed by · Agents
- [Knowledge Base Agent](/Agents/Knowledge_Base_Agent) — consumed by · Agents
- [Support Triage Agent](/Agents/Support_Triage_Agent) — consumed by · Agents

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