01Speckle
Data interoperability platform for AEC
- →Open source
- →Excellent integrations
- →Version control
All buyer's guides
Buyer's guide
Best AEC Data & Interoperability Tools (2026)
The connective layer: getting project data out of silos and into use.
Every AI ambition in AEC eventually hits the same wall: the data is scattered across authoring tools, PM platforms, ERPs, and file shares that don't talk. This category is the connective layer: model exchange (Speckle), integration APIs (Agave), managed warehouses with construction data models (Kroo), BI on BIM (VIM), and AI agents that work across it all (Datagrid, Nomic).
It's the least glamorous category and the highest-leverage one: firms that fix their data layer get compounding returns from every tool bought afterward. If your AI pilots keep stalling on 'we can't get the data,' start here, not with another point solution.
What to look for
- Open standards and export rights: the interoperability layer must not become the new lock-in
- Pre-built connectors for your actual systems (Procore, P6, Sage, Revit versions)
- Who maintains the pipes: managed service vs your own developers
- AI-readiness: structured, queryable data is the point, can agents work against it?
The tools (7)
02Agave
Single API to connect any construction software, Procore, BIM 360, Sage, and more
- →Unified construction API
- →Reduces integration complexity
- →Connects 20+ platforms
03Kroo
Pre-built connectors and a managed warehouse unify ERP, PM and scheduling data into one source of truth, with AI enterprise search on top.
- →Pre-built connectors for Procore, P6, Sage, CMiC, Vista and more
- →Managed warehouse with unified construction data models
- →Kris AI enterprise search over the unified data
04VIM
BIM data in Microsoft Power BI
- →Business intelligence
- →Power BI integration
- →Data transformation
05Datagrid
AI agents that connect to project systems and automate data work across construction documents and workflows. Acquired by Procore in 2026.
- →AI agents work across submittals, specs, RFIs and schedules
- →Connectors to common construction systems
- →Acquired by Procore (2026) to power agentic workflows
06Nomic
AI agents that run quality control and coordination review across a firm's own drawings, specifications, and project files. They read a whole set rather than one sheet at a time, which is where coordination errors live, and return a list of findings with a sheet reference for a reviewer to confirm. Covers drawing review, submittal review against the specification, RFI research over the project archive, building code checks, and plain-language search of past projects. Nomic also wrote AEC-Bench, the open benchmark for AI on coordination work, so the company has published what its own and other agents can and cannot do.
- →Works across a full drawing set and its specifications together, rather than one sheet at a time, which is where coordination errors actually appear
- →every finding carries a sheet and specification reference so a reviewer can confirm it
- →ready-made agents for drawing review, submittal review, RFI research, code checks, and knowledge search, so there is no prompt engineering to do
07Layer
Layer is a no-code workflow platform to collect & capture data from anywhere on any device.
- →No-code data capture
- →Any-device field workflows
- →Revit integration
Frequently asked questions
Why start with data instead of AI tools?
Because every AI tool's ceiling is the data it can reach. Firms with unified, structured project data get more from every subsequent purchase; firms without it keep buying point solutions that can't see each other.
Do small firms need a data layer?
Small firms need organized cloud documents and consistent standards more than a warehouse. The dedicated data layer starts paying off with multiple systems, multiple offices, or serious BI ambitions, typically 50+ people.
Before you pick a tool
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