AI schedule builder for CPM schedules with evidence and XER export
Specialized agents draft a CPM schedule from project documents and client answers, show the evidence behind each activity, and export XER for the scheduler to review.
The problem
Building a baseline schedule means reading hundreds of pages and chasing the client for answers only they have. Two schedulers given the same project produce two different schedules, and neither can easily show why an activity exists or where its duration came from.
What we build
We split scheduling into steps and give each one to a narrow agent: an info sheet of what is being built, a tracked set of means-and-methods questions the client can answer through a secure link, and a schedule builder that produces a health-scored draft with activity evidence and XER export. The scheduler reviews and approves every draft. This is how Connect, the platform we built for Syncify, works in production.
How it works
- 1
Build the project info sheet
An agent reviews the drawings, specs and meeting transcripts assigned to the project and normalizes what is being built into one info sheet the scheduler can edit and save.
- 2
Answer the means and methods questions
A second agent produces the questions only the client can answer. The scheduler answers them or sends a secure, password-protected link, and client answers come back marked client verified.
- 3
Generate a draft schedule
The schedule builder uses the info sheet, answers, files and any basis-of-schedule standards to draft a baseline, RFI/RFP or new-build CPM schedule. In the Connect walkthrough a build takes roughly 10 to 15 minutes.
- 4
Test, review and export
Each draft runs through checks that produce a health score, every activity keeps the evidence behind it, and versions are kept. The scheduler fixes failures with the builder, reviews critical and driving paths, and exports XER.
- Syncify
- Oracle Primavera P6 and XER files
- Project drawings and specs
- Model Context Protocol (MCP)
- Next.js and Python
The value it creates
Time saved
Measured by timing recent baseline schedules built the current way against the same scope drafted with the agents and reviewed by a scheduler.
Standardization
Every schedule follows the same procedure from info sheet to questions to draft, so output no longer depends on which scheduler picked up the job.
Better decisions
Activity evidence and client-verified answers show why each activity and duration exists, so a schedule can be defended with the record.
Early warning
The health score and checks flag logic and structure problems in a draft before it reaches the client.
Proof
Related use cases
- Built and shown
AI assistant for project drawings, specs and documents
Ask questions of a project's drawings, specs and meeting notes and get answers that cite the file and passage they came from.
- Built and shown
AI sales automation: lead capture, research, follow-ups and proposals
Agents handle the research, scheduling and first drafts around each sales step, a person approves anything customer-facing, and the CRM stays up to date.
- Built and shown
MCP servers for Procore, Primavera P6 and other construction systems
An MCP server exposes a construction system's API as tools an AI agent can call, with scoped permissions and a log of every call.
Frequently asked questions
Does the AI replace the scheduler?
No. The agents do the document review, question tracking and first draft. The scheduler sets the drivers, reviews the critical and driving paths, fixes what the checks flag and approves the schedule before it goes anywhere.
Can the schedule be opened in Primavera P6?
Yes. The builder exports XER, the file format P6 imports, and a revised schedule can be imported back so the agents work from the latest version.
How do you stop the agent making up durations or logic?
Every activity keeps the evidence it was based on, the client answers anything the documents cannot, and each draft runs checks that produce a health score. Quality rubrics and reference sets in the admin portal are used to review agent output over time.
Do we need Syncify to use this?
Connect was built on Syncify's CPM engine. For another team we would scope the same agent pattern around the scheduling tools you use, starting with an AI readiness review of your schedule types and documents.
Next step
Which report or workflow would you like to improve?
Tell us what your team does today, which systems are involved, and what you want to change. We'll discuss whether there is a practical fit.
Prefer email? charley@buildflows.ai