Kredete - Data Pipeline

1 Data sources & ingestion layer

Structured sources

PostgreSQL (transactional)

MongoDB (user profiles)

Redis (session/cache)

Partner APIs (REST)

Payment processor feeds

Unstructured sources

Chat transcripts

Support tickets

KYC documents (PDF)

Email communications

Voice call recordings

Streaming sources

Kafka topics (events)

WebSocket connections

CDC (Debezium)

Webhook receivers

Real-time FX feeds

External feeds

Credit bureau (batch)

Market data (Reuters)

Sanctions lists (daily)

Regulatory updates

Partner reconciliation

Ingestion patterns

Real-time (< 100ms)

Near real-time (< 5min)

Micro-batch (15min)

Batch (hourly/daily)

On-demand (API pull)

Throughput: 50K events/sec

2 Data preparation & cleaning

Schema validation

JSON Schema enforcement

Type coercion

Required field checks

Enum validation

Version compatibility

Cleaning operations

Deduplication (hash)

Null handling

Outlier detection

Format normalization

Encoding standardization

Transformation

Currency normalization

Timestamp UTC conversion

Address standardization

Name canonicalization

Amount rounding rules

PII handling

PII detection (NER)

Tokenization

Masking (last 4 digits)

Encryption at rest

Consent-based access

Dead letter queue

Failed record capture

Error classification

Retry logic (3x exp)

Alert on threshold

Manual review queue

DLQ rate: 0.02%

3 Tagging, enrichment & classification

Entity tagging

NER (people, orgs, locations)

Transaction categorization

Merchant classification (MCC)

Risk category assignment

Corridor tagging

Semantic enrichment

Sentiment scoring

Intent labeling

Topic classification

Language detection

Urgency scoring

Graph enrichment

User relationship mapping

Transaction graph

Device fingerprint links

Beneficiary clustering

Risk propagation

Feature engineering

Rolling aggregates (7d/30d)

Velocity features

Time-series features

Cross-entity features

Embedding features

Features generated: 847

4 Embedding generation & vectorization

Text embedding

OpenAI ada-002

Cohere embed v3

Sentence-BERT (local)

Chunk strategy (512 tok)

Overlap (64 tok)

Document processing

PDF extraction (OCR)

Table parsing

Image captioning

Markdown conversion

Metadata extraction

Chunking strategies

Semantic chunking

Recursive character split

Sentence boundary

Token-based (tiktoken)

Parent-child hierarchy

Quality assurance

Embedding drift detection

Similarity distribution

Coverage analysis

Dimensionality check (1536d)

Batch vs incremental

Index management

HNSW index build

IVF clustering

Namespace partitioning

TTL-based expiry

Re-indexing schedule

Vectors stored: 12.4M

5 Data storage & serving layer

Vector database

Pinecone (primary)

Weaviate (secondary)

Cosine similarity search

Metadata filtering

Multi-tenancy (namespace)

Vector cache API

Redis vector cache

Semantic dedup

Hot query cache (LRU)

TTL: 1h (dynamic)

Cache hit rate: 68%

Relational store

PostgreSQL (OLTP)

TimescaleDB (time-series)

Read replicas (3x)

Connection pooling

Partitioning (monthly)

Data lake

S3 (raw/bronze)

Parquet (silver)

Delta Lake (gold)

Data catalog (Glue)

Lifecycle policies

Serving APIs

REST API (search)

gRPC (internal)

GraphQL (aggregations)

Batch export (CSV/Parquet)

Streaming (SSE)

Query latency: 8ms p50

6 Data controls, compliance & observability

Access control

RBAC (role-based)

ABAC (attribute-based)

Row-level security

Column masking

API key rotation

Compliance

GDPR (EU)

CCPA (California)

Right to deletion

Data portability

Consent management

Privacy

Differential privacy

K-anonymity

Data minimization

Purpose limitation

Retention schedules

Lineage & catalog

Data lineage graph

Impact analysis

Schema registry

Data dictionary

Ownership mapping

Monitoring

Pipeline health (DAG)

Data freshness SLA

Quality score dashboard

Anomaly detection

Cost attribution

SLA compliance: 99.7%

Kredete Shared Data Platform — Ingestion & Processing Pipeline