Platform
From intent to trusted data.
Three AI copilots help you connect, transform, and map data in plain language. A frontier model reasons about your intent while the Nexadata engine does the work, deterministically, so trusted data lands in your target system and raw data never leaves the platform.
The pipeline
One continuous flow, from source to trusted data
Connect, transform, map, review. Each step is guided by a no-code copilot, and you approve the plan before anything runs.
- 01
Connect
Point at any OpenAPI or OData system. The Connector Copilot reads the spec and builds a working connection.
- 02
Transform
Describe the change in plain English. Joins, aggregations, and enrichment are proposed as a plan you approve.
- 03
Map
Align source and target schemas, including conditional account logic, drafted in seconds and validated by you.
- 04
Review
Human-in-the-loop checks, full lineage, and audit history before trusted data lands in your target system.
Three copilots, one AI architecture
Three specialties holding up one platform
There are exactly three copilots, each a different AI specialty. Together they form a single trusted pipeline, with a human reviewing every step.
Connector Copilot
Connect
Reads any OpenAPI or OData spec, understands endpoints, parameters, and pagination, and generates a working dataset configuration. No integration code, no static connector library to wait on.
“ Connect to Coupa and pull our open requisitions. ”
Transform Copilot
Transform
Translates plain-English intent into a sequence of Nexadata transformation primitives, joins, aggregations, validations, and enrichment. You see the proposed plan before anything runs.
“ Join our three CRM datasets and dedupe by account. ”
Mapping Copilot
Map
Reads source and target schemas, infers the semantic relationships, and proposes the conditional logic to align them. Complex if/then mappings drafted in seconds, validated by you.
“ Map to Deferred Revenue when Product Type = Subscription and Term > 12 months. ”
The fourth step, Review, is the human checkpoint, not a copilot. Nothing runs against your data until a person approves the plan.
The reasoning handshake
A model reasons. The platform executes.
Every workflow is an agentic loop across two layers. A frontier model interprets and plans; the Nexadata engine validates and runs. Only abstracted context reaches the model, never your raw records.
The reasoning layer
A frontier model, Anthropic Claude
- 1 Receives intent in plain language
- 2 Interprets the goal
- 3 Plans the approach
- 4 Makes tool calls to the platform
The execution layer
The Nexadata platform, tokenless
- 1 Evaluates and validates the plan
- 2 Executes with native primitives
- 3 Deterministic, auditable, governed
- 4 Delivers trusted, prepped data
Expanded ecosystem
If it has an OpenAPI or OData spec, you can connect it
The Connector Copilot reads a system’s own specification and stands up a live connection, so you reach the long tail of sources without waiting on a static connector to be built.
Cloud applications
EPM, CRM, FIN & ERP, HCM, and databases, reached through the Connector Copilot.
Cloud storage
Google Drive, OneDrive, Amazon S3, Azure Blob, and SFTP.
Semi-structured
Excel, Google Sheets, and CSV, parsed into clean, typed tables.
Unstructured
PDFs and document tables, turned into structured rows you can model.
Proof at enterprise scale
8.7M GL records, harmonized in 22 seconds
One workflow joined GL transactions with department lookups, account mapping tables, and reference data, then summarized to the right granularity for planning, analytics, and reporting.
8.7M
source GL records
22s
end to end
876K
harmonized output rows
74 MB
from 470 MB in
That single workflow handled joins, aggregations, derived columns, conditional account mapping, formatting, and UUID key generation. Deterministic, repeatable, and auditable at scale.
Technical foundation
An engine built for enterprise data
The platform pairs a fast, deterministic data engine with open APIs and an MCP server, so it fits the stack you already run.
Cloud-agnostic
Deployable on AWS, Azure, or GCP, with a monolithic, containerized service. Currently hosted on AWS.
Parallelized data engine
A tokenless, deterministic engine that processes structured, semi-structured, and unstructured data at scale.
Public and private REST APIs
Documented REST APIs so Nexadata fits into the stack and orchestration you already run.
MCP Server
Build and execute workflows, manage connections, and read datasets from any MCP-capable AI client.
No-code AI interface
Every copilot is driven in plain language, so business users build pipelines without scripts.
Built-in observability
Lineage, audit history, and run telemetry on every workflow, so you can trust and trace each result.
The certifications and access controls, SOC 2 Type II, zero data retention, and SSO / SAML / RBAC, are covered on the Security page.
See the platform on your data
Start free with your first use case, or talk to us about your EPM and planning stack.