Nexla

What Nexla does

Nexla is an enterprise-grade, AI-powered data integration platform for agents that unlocks data from any source and transforms it into production-ready data products for AI and agents. With support for 1000+ pre-built connectors and multiple integration styles – including ELT, ETL, streaming, APIs, and agentic RAG – Nexla enables teams to build and manage data flows without writing code. It processes over one trillion records per month across industries, providing connectivity, context, and governance for AI apps and agents. Nexla helps enterprises transform fragmented data into agent-ready data that AI applications and agents can trust, connecting to any source, enriching data with business context, and delivering governed data products through APIs, pipelines, MCP servers, and AI workflows.

Products

• Nexla PlatformAn enterprise-grade, AI-powered data integration platform for agents that unlocks data from any source and transforms it into production-ready data products for AI and agents. It supports 1000+ pre-built connectors and multiple integration styles including ELT, ETL, streaming, APIs, and agentic RAG.
• Nexsets (Data Products)Human-readable, virtual data products that turn any source with unstructured or structured data into a logical data model independent of formats, protocols, and data speeds. Nexsets encapsulate schema, sample data, data validation, error management, audit logs, and access control, making data ready-to-use and AI-ready.
• MCP StudioAllows users to describe what their agents should do, and it builds the MCP server for them. It probes connected systems, discovers candidate data entities, assembles governed tools, and enforces policy without writing integration code.
• Agent Data SDKA software development kit for agents to interact with data, part of the delivery mechanisms of the Nexla platform.
• Helix Context LayerNexla’s context layer that unifies Nexsets, enterprise documents, reference data and ontologies, pipeline history, and web search to enrich raw data with context for agents.
• Express by NexlaA tool that allows users to describe data pipeline requirements in plain English, and it automatically builds the pipeline, connects sources, configures transformations, sets up scheduling, and applies governance. It includes an MCP server for AI agents to create data integrations on demand.
• Nexla Orchestrated Versatile Agents (NOVA)An agentic interface within the Nexla UI that allows LLMs to directly query Nexset data and metadata for analysis, building transforms, new Nexsets, and end-to-end flows.

Key capabilities

• 1000+ bidirectional connectors
• Support for ELT, ETL, streaming, APIs, and agentic RAG
• No-code data flow building and management
• AI-powered data integration
• Production-ready data products (Nexsets)
• Data layer for enterprise AI and agents
• Connectivity, context, and governance for AI apps
• Automated data product generation
• Schema management
• Dataset annotation
• Column level lineage
• Automated data characterization
• No-code excel-like functions for data preparation
• Record level filtering
• Validation rules (existence of fields, regex, data type, values)
• Custom functions (Python, JS)
• Error notifications in-app and email
• Automated Error Quarantine with full diagnostics
• Custom notifications
• SLA Guarantees
• Team and Organization management
• Advanced REST API (Custom Auth - OAuth, JWT, HMAC, API chaining)
• Custom API Templates
• Support for AVRO, Parquet, ORC, EDI data formats
• Streaming Sources and Destinations (Kafka, Google Pub/Sub)
• Create and manage teams
• Nexset sharing at individual or group level
• Advanced Permissions to pipelines, datasets, and other entities
• Schema templates
• Shared Data Prep functions
• Extensible function library
• Static and Dynamic Lookups
• Full IDE for Python and Javascript custom functions with test harness
• Metadata transformations
• Audit Log
• SOAP API support
• Role based data source authentication
• Real time data: API Proxy, Data API
• Custom Sources and Destinations
• Nexla API Access to 100+ APIs
• Nexla command line (CLI) tool
• Nexla Python SDK
• High speed Pipeline options (2X, 4X, 8X)
• Private VPC Deployment (AWS, GCP, Azure, On-premise)
• Integration with Data Governance and Data Catalog tools
• Multiple federated data backplanes
• VPN Tunnel
• OIDC and SAML2.0 SSO (Okta, Auth0, Active Directory)
• Metadata intelligence for auto-generating Nexsets
• Continuous metadata analysis and record-level data analysis
• Always up-to-date and versioned Nexsets
• Data validation rules for data quality
• LLM querying of Nexset data and metadata
• Unified data model in a private marketplace
• Support for all integration styles: ELT/ETL, change data capture (CDC), replication, R-ETL, API integration, streaming, (S)FTP, GenAI RAG, BYO integration
• Pre-configured integration templates
• Agentic Probe for data structure and business relevance discovery
• MCP Gateway for agent data requests
• Bidirectional connectors for read and write actions
• Zero-Trust by Default security for connectors
• LLM Connectors (OpenAI, Anthropic, Azure AI Studio, Google Gemini, Cohere, Mistral AI, Grok by xAI, NVIDIA AI, Hugging Face TGI, Ollama API, Perplexity AI)
• Vector DB Connectors (Pinecone, Vespa, Qdrant, Weaviate, Milvus)
• Encrypt data at rest and in motion
• Fine-grained access control
• Integrated Identity and Access Management (SAML, OIDC)
• Private and Hybrid Cloud Deployment options
• Native authentication and authorization for connectors/APIs (TLS1.2, SSH-2, IPSec, Oauth, HMAC, JWT)
• Enhanced Privacy (PII protection, data hashing, custom validation policies)
• Secure in Development (no data records stored, data sampling, redaction/obfuscation)
• Local Data Processing options (SSH, VPN, Bastion host)
• Advanced Secrets Management (built-in credential vaulting, BYO vaulting)
• End-to-End Lineage and Audit Trails
• Continuous Security Vulnerability Testing
• Prompt-to-Pipeline Intelligence (Express)
• Instant iteration and re-prompting for pipeline changes (Express)
• Auto-Governed Data Products (Express)
• MCP-Native and Agent-Ready by Default (Express)
• Write-Back Included (Express)

Use cases

• Building agent data layers
• Providing connectivity, context, and governance for AI apps and agents
• Transforming raw data into production-ready data products for AI
• Automating data flows without writing code
• Analyzing and executing customer renewals (MCP Studio example)
• Analyzing Google Ads data with Claude using an MCP server
• Moving data from PostgreSQL to Vespa.ai
• Building live dashboards from data sources like Cricbuzz to Google Sheets
• Automating game deal notifications using APIs and webhooks
• Monitoring exchange rates and triggering email alerts
• Building currency data pipelines to Snowflake
• Automatically transforming and migrating Salesforce cases into ServiceNow incidents
• Pushing aging Salesforce opportunities to Slack
• Automating PDF extraction for insurance claims to MySQL
• Building Amazon S3 to Snowflake data pipelines
• Moving vector data from Pinecone to Vespa.ai
• Enabling 360 visibility for portfolios and assets in asset management
• Automating risk management in asset management
• Accelerating partner and customer onboarding in asset management
• Streamlining processes and delivering self-service in asset management
• Enhancing and automating compliance in asset management
• Turning notes and pictures into data products (Nexsets)
• Personalizing customer experience in asset management
• Improving settlement processes in asset management
• Automating compliance reporting (Solvency II, IFRS 17) in asset management
• Accelerating partner integration (e.g., retail partners for Instacart, Glovo)
• Enabling Retrieval Augmented Generation (RAG) for eCommerce customer experience
• Preventing IoT Analytics Downtime
• Delivering Real-time Inventory Data with NetSuite
• Expanding Connectivity across CRM Tools
• Improving end-to-end customer experience in financial services
• Gaining 360 customer visibility in financial services
• Accelerating partner and customer onboarding in financial services
• Streamlining processes and delivering self-service in financial services
• Enhancing and automating compliance in financial services
• Turning documents into data products in financial services
• Enhancing risk management in financial services (portfolio, asset, currency data)
• Detecting and managing fraud in financial services
• Automating compliance reporting (Cyber Security, ESG, AML) in financial services
• Feeding governed data to machine learning training pipelines, scoring models, and AI enrichment services
• Routing governed data to large language models for enrichment, summarization, classification, or generation
• Powering context engines for AI agents (semantic search, RAG, memory)
• Building comprehensive and secure patient profiles with real-time data in HealthTech
• Integrating, transforming, delivering, and monitoring data in HealthTech
• Creating seamless, real-time data connectivity across operational domains with biomedical data and healthcare reports
• Working with HL7 FHIR Servers and data standards
• Working with Biomedical (IoMT) and Healthcare Data (EHR)
• Revenue reporting pipelines from multiple sources
• Real-time customer data feeds for LLM agents
• Moving, transforming, and staging enterprise data from any source into governed data products for agents, analytics, and operations
• Consolidating ETL, ELT, and Reverse ETL on one platform
• Syncing enriched warehouse data back into operational systems (e.g., Salesforce, HubSpot, SAP)

AI approach

Nexla provides an AI-powered data integration platform that transforms raw data into production-ready data products for AI applications and autonomous agents. It uses AI to automate pipeline building, schema detection, transformation recommendations, and governance. The platform supports agentic RAG, conversational UI for building MCP servers, and integrates with various LLMs and vector databases. It also uses AI for generating transform logic and understanding data engineering intent from natural language.

Tech named: LLMs, Retrieval Augmented Generation (RAG), MCP (Multi-Agent Communication Protocol) Gateway, Helix Context Layer, Nexsets, Agentic Probe, OpenAI, Anthropic, Azure AI Studio, Google Gemini, Cohere, Mistral AI, Grok by xAI, NVIDIA AI, Hugging Face TGI, Ollama API, Perplexity AI, Pinecone, Vespa, Qdrant, Weaviate, Milvus, Claude

Industries served

• Software Development
• Asset Management
• Financial Services
• Insurance
• Retail
• eCommerce
• Government
• HealthTech
• Healthcare IT
• Media
• IT Services
• Healthcare & BioTech
• Energy & Utility
• Transportation

What it says sets it apart

• AI-powered data integration platform for agents
• 1000+ pre-built bidirectional connectors
• Support for all integration styles (ELT, ETL, streaming, APIs, RAG, CDC, R-ETL, BYO)
• No-code platform for building and managing data flows
• Transforms raw data into production-ready, AI-ready data products (Nexsets)
• Provides connectivity, context, and governance for AI apps and agents
• Processes over one trillion records per month
• MCP Studio for conversational agent server building
• Helix Context Layer for data enrichment
• Express by Nexla for prompt-to-pipeline creation
• NOVA (Nexla Orchestrated Versatile Agents) for LLM interaction with Nexsets
• Truly bidirectional connectors (read and write)
• Zero-Trust by Default security for connectors
• Integrated LLM and Vector DB connectors as first-class citizens
• End-to-end data protection with encryption, fine-grained access control, and integrated IAM
• Private and Hybrid Cloud Deployment options
• Enhanced PII privacy with data hashing and custom validation
• End-to-End Lineage and Audit Trails
• SOC 2 Type II, GDPR, and CCPA compliant
• Instant iteration and re-prompting for pipeline changes with Express
• Auto-Governed Data Products with full lineage, metadata, and access controls
• Consolidates ETL, ELT, and Reverse ETL on a single platform
• AI connector builder ships new connectors in under a week
• AI prompts to generate transform logic
• Supports structured, semi-structured, and unstructured data