Skip to main content

Xfactr.ai

How can we help you?

data platforms

One platform. Every source.
AI-native.

Not a data warehouse with AI bolted on. A platform built from the ground up

for models, agents, and RAG retrieval alongside dashboards and SQL.

 

Talk to Our Team
↗ Consume

AI Models · LLMs · Dashboards · Agents

MCP · REST API · SQL · RAG retrieval

↗ Semantic

Universal Semantic Layer

AtScale · dbt Semantic · NLQ Interface

✦ Vector / AI

Embeddings · Feature Store · Vector Search

Pinecone · pgvector · Weaviate · Feast

↗ Processing

Lakehouse · Warehouse · Streaming

Snowflake · Databricks · Delta Lake · Iceberg

↗ Sources

ERP · CRM · IoT · Docs · APIs · Legacy

SAP · Salesforce · Sensors · S3 · REST

Six things we build

Platform capabilities.
Not vague promises.

Lakehouse & Data Mesh Architecture

Unified storage for analytics, AI and streaming with Delta Lake & Iceberg.

SnowflakeDatabricksBigQueryDelta LakeIcebergData Mesh

Unified Source Access

ERP, CRM, IoT and APIs through one governed layer.

SAPSalesforceMQTTREST

Platform Modernisation

Legacy to cloud migration.

AssessRoadmapMigrate

Agentic Data Access

MCP layer for secure AI access.

MCPLangGraphGoverned

Vector DB & RAG Integration

Enterprise embeddings for grounded retrieval.

PineconepgvectorWeaviateQdrantLangChain

✦ AI-native access layer

Your data. Any AI. Governed end to end.

The same data lake that runs your Power BI dashboards also serves your LLMs, copilots, and autonomous agents via a controlled retrieval layer with RBAC, rate limits, and full audit trails. One platform. Multiple access patterns.

  • ✦ Embedding pipelines at ingest
  • ✦ RAG for grounded LLM responses
  • ✦ Semantic search across all content
  • ✦ AI agent data access via MCP
  • ✦ RBAC + audit on every query
RAG PIPELINE
Contracts
Reports
Records
Policies

✦ Embedding Model

text-3-small   •   ada-002

✦ Vector Store

Pinecone   •   pgvector   •   Weaviate

LLM + Retrieved Context

Claude   •   GPT-4o   •   Gemini

Grounded Response + Citations

What we connect to.

The exact stack. Production proven.

LAKEHOUSE
Snowflake Databricks BigQuery Delta Lake Iceberg Redshift
✦ VECTOR / AI
Pinecone pgvector Weaviate Feast LangChain MCP Server
SEMANTIC
AtScale dbt Semantic Cube.dev MetricFlow
GOVERNANCE
Unity Catalog Purview Collibra Apache Atlas OpenLineage

One

Storage layer serving SQL analytics, ML training, and LLM RAG retrieval simultaneously

AI-native

Vector store, feature layer, and agentic access designed in from day one not added later
 

Governed

Full RBAC, lineage, and audit on every AI model’s data access including LLM retrieval queries

Where these capabilities apply

Edge-to-Cloud AI across our platforms and services.

SERVICE
Data Engineering
The pipelines that deliver data into this platform.
→ data-engineering
SERVICE
Analytics & Governance
BI and governance on top of this platform layer.
→ analytics-governance
CAPABILITY
AI & Agentic AI
Agents that access enterprise data through MCP and API layers.
→ ai-agentic-ai
SERVICE
MLOps
Model training pipelines and feature store management.
→ devops-mlops

Connect With us

Build the platform your AI actually needs.

 Tell us your sources, destinations, and latency requirements.

Book a Call