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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesChoose construction software by proving that it supports your real workflows and data, then test one controlled AI-agent workflow before committing. An impressive AI demo is not enough: the platform must expose the project records an agent needs, move data in the right direction at the required cadence, enforce your permissions, and leave an audit trail.
This guide gives you a requirements-led way to shortlist construction platforms, verify API and connector claims, compare agent maturity, and run a pilot using your own documents and field processes.
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1. Map the construction workflows you actually need
Begin with the project lifecycle, not a list of AI features. Autodesk’s construction integration documentation separates document and file management, project management and scheduling, financial planning, site and safety management, and data analytics. Those categories are a useful starting map, but your company may also need preconstruction, quality, procurement, commissioning, handover, or facilities operations.
Build a workflow inventory
For every workflow, record the system of record, the people who use it, the decisions that depend on it, and the data an agent would need to read or write. A workflow that sounds suitable for AI may fail if its source records are incomplete, poorly structured, or inaccessible through an API.
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| Workflow area | Questions to answer | Data an agent may need |
|---|---|---|
| Preconstruction | How are estimates, bids, scopes, and clarifications created and approved? | Bid packages, drawings, specifications, qualifications, estimate revisions, approval history |
| Document and file management | Where are the current drawings, submittals, RFIs, contracts, and correspondence stored? | Files, revisions, metadata, transmittals, permissions, approval status |
| Scheduling | Which schedule is authoritative, and how are updates, dependencies, and delays recorded? | Activities, calendars, predecessors, progress, constraints, baseline and current dates |
| Field execution | How do supervisors capture observations, quantities, photos, and daily reports? | Mobile forms, images, video, locations, cost codes, labor and equipment records |
| Quality and safety | How are inspections, incidents, corrective actions, and closeout items assigned? | Checklists, observations, incident details, responsible parties, due dates, evidence |
| Cost and financial control | How are commitments, change orders, invoices, forecasts, and cost-to-complete figures reconciled? | Commitments, budgets, cost codes, invoices, approvals, forecast versions |
| Handover and operations | What information must be delivered to the owner or operations team? | Asset registers, warranties, commissioning records, as-built models, manuals, maintenance data |
Separate essential workflows from useful experiments
Mark each workflow as essential, important, or experimental. Essential workflows should determine the shortlist. Experimental ideas—such as asking an agent to summarize a meeting—can be tested later, but they should not compensate for missing schedule, cost, document, or field capabilities.
2. Translate each workflow into an integration requirement
“Has an API” is too vague to be a buying criterion. You need to know what the API or connector exposes, how data moves, how often it moves, and what an agent is allowed to do with it.
Specify direction, detail, and cadence
- Direction: Can data flow into the construction platform, out to another system, or both? A one-way export will not support an agent that must update a record.
- Detail: Does the interface expose individual fields, relationships, revision history, locations, and permissions, or only a document download or aggregate report?
- Cadence: Is the flow real time, event-driven, continuous, hourly, daily, or manually triggered? A daily batch may be adequate for accounting but unsafe for a field issue that requires immediate escalation.
- Scope: Can access be limited to a tenant, project, folder, model, cost code, or user role?
- Write behavior: Can the integration create, update, approve, or delete records? If it can write, what confirmation step is required?
Compare the available integration patterns
| Pattern | Best use | Questions for the vendor |
|---|---|---|
| Native connector | A common system that the platform already supports | Which objects and fields are supported? Are writes supported? Who maintains version changes? |
| Marketplace application | A packaged integration supplied by the platform or a partner | What security review was performed? Who provides support, monitoring, and incident response? |
| No-code or iPaaS flow | Scheduled or continuous transfers across several business systems | What triggers and transformations are available? How are retries, failures, and credentials handled? |
| Public API and webhooks | A custom agent or internal integration that needs precise control | What are the rate limits, event coverage, pagination rules, version policy, and sandbox options? |
| Custom or niche integration | A specialized application not covered by a standard connector | Who owns the code, testing, hosting, monitoring, and maintenance when either platform changes? |
Autodesk describes Autodesk Construction Connect as a no-code integration service powered by Workato, with continuous or scheduled data flows. Its examples include QuickBooks Online, Sage Intacct, Xero, Acumatica, DocuSign, Salesforce, Microsoft Dynamics, Smartsheet, Excel Online, Google Sheets, and Box. Treat those examples as starting points, not proof that every object, write operation, plan, or region is supported. Verify the exact connector and field coverage for your account.
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3. Verify what “AI-agent integration” means today
Agent access is changing quickly. A vendor may use “AI,” “copilot,” “agent,” or “MCP” for capabilities with very different permissions and maturity. Ask for the precise status and test it in your tenant.
Use a maturity ladder
| Status | What it means for a buyer | Evidence to request |
|---|---|---|
| Generally available | Published for production use under stated terms | Current documentation, supported regions and plans, service limits, support process, change policy |
| Beta or early access | Usable by selected customers but subject to change and incomplete coverage | Entry criteria, data-handling terms, production restrictions, exit plan if the feature changes |
| Technical preview | Useful for evaluation, not a dependable production commitment | Supported scenarios, known limitations, retention policy, expected migration path |
| Announced or roadmap | A stated intention, not an available capability | Do not count it in the business case until you can test it |
What the March 2026 Procore announcement establishes
In “Building the Foundation for AI in Construction: The Next Era of the Procore Marketplace & APIs,” dated 2 March 2026, Procore said it was developing Agentic APIs on Datagrid for deep search across PDFs, images, and videos and for agents to act across software workflows. The announcement said those APIs were in testing and targeted general availability in late March 2026. That was a dated target, not confirmation that the APIs are generally available now.
The same announcement described a revised managed marketplace review covering strategic fit, technical feasibility, and security compliance. It also said third-party integrators could continue to provide custom or niche integrations outside the public Marketplace. Procore reported more than 500 integrations in that post; this is a vendor-reported figure from March 2026, not an independently audited current count.
A vendor-described pre-beta example involved Track3D. The example uses field video to extract installed quantities and spoken observations into structured reports, map progress to cost codes and locations, and combine the results with schedule and manpower information for forecasting. It demonstrates a possible workflow, not an independent measure of accuracy or savings.
“We plan to be transparent about real-time agent activity to enable user and enterprise control, auditing, logging and transparency.”
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Brint Markle, Head of Global Ecosystem Partnerships at Procore, and Michael Marfise, VP of Product, Platform and Ecosystem at Procore, in the 2 March 2026 announcement.
Procore’s developer portal labels AI-agent and MCP capabilities as coming in 2026. During procurement, ask the vendor to identify which parts are live in your edition and which remain in testing or on the roadmap.
What the April 2026 Autodesk update establishes
Autodesk Platform Services’ “Building for Agentic AI: What’s New in Autodesk Platform Services,” dated 15 April 2026, described the AEC Data Model API as providing access to granular Revit geometry, properties, and relationships. That level of structure matters when an agent must answer questions about model elements rather than merely search filenames.
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The update distinguished several MCP capabilities by status:
- Fusion MCP, Fusion Data MCP, Revit MCP, and Product Help MCP were described as technical previews.
- Fusion Compute MCP was described as private beta.
- InfoWorks MCP was described as coming soon.
It also stated that three-legged OAuth was available at that time for the Forma Admin API and APS Data Management API and was coming to other APIs. OAuth scope, consent, and project boundaries should be verified for the exact API your agent will use; availability is API- and version-specific.
The live Autodesk AECO technology partner directory lists data-integration and AI examples such as Agave, ProjectReady, BIMLOGIQ, and Bimmatch. Directory inclusion shows that an ecosystem entry exists; it does not prove that a listed application meets your requirements, is available in your geography, or has a commercial relationship with your company.
4. Make governance a buying requirement, not a later review
An agent that can search project records or change a workflow is another identity operating inside your environment. Evaluate controls at the same time as capability.
Questions about identity and permissions
- Which user, service account, or delegated identity does the agent use?
- What OAuth scopes are requested, and can they be reduced to least privilege?
- Can access be limited by tenant, project, company, folder, model, or record type?
- Does the agent inherit the user’s permissions, or does it use a broader administrative account?
- How are consent, credential rotation, revocation, and offboarding handled?
Questions about actions and approvals
- Which records can the agent read, create, update, approve, or delete?
- Can high-impact actions—such as issuing a change, approving a cost item, or closing a safety action—require a named human approval?
- Can you configure read-only mode for the pilot?
- Are proposed changes shown to a user before they are committed?
Questions about evidence and incidents
- Are prompts, retrieved records, tool calls, proposed actions, approvals, and final changes logged?
- Can an administrator see activity in a usable audit export?
- How long are logs and agent inputs retained, and where are they stored?
- Are customer data and model-training use separated by contract and configuration?
- What is the notification and recovery process for a mistaken update, exposed credential, or vendor incident?
- How are marketplace applications reviewed for security and privacy before installation?
Require written answers and sample audit records. A statement that an agent is “secure” is not a substitute for knowing exactly what it can access and change.
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5. Score shortlisted platforms with one requirements matrix
Use the same evidence for every option. A simple score is useful only when each score is backed by a document, demonstration, or pilot result.
| Criterion | Evidence to collect | Suggested decision test |
|---|---|---|
| Workflow coverage | Feature map across preconstruction, documents, field, schedule, quality, safety, cost, handover, and operations | All essential workflows have a supported system of record |
| Data access | API schemas, model relationships, document metadata, images, video, revision history, and permissions | The intended agent can retrieve the exact records and context needed |
| Integration mechanics | Native connectors, marketplace apps, no-code flows, webhooks, public APIs, and custom options | There is a supported path with an identifiable owner for monitoring |
| Agent maturity | General availability, beta, preview, or announcement status for each proposed feature | The business case relies only on capabilities you can use and support |
| Identity and controls | OAuth scopes, consent, tenant and project boundaries, approvals, logs, retention, and residency | Controls meet internal policy before production access is granted |
| Field usability | Mobile workflow, offline behavior, device support, upload time, and connectivity requirements | Field staff can complete the task at the point of work |
| Implementation effort | Migration, mapping, configuration, integration build, testing, training, and administration | Named people and realistic time are available for delivery |
| Total cost | Licenses, modules, integration setup, migration, training, administration, and ongoing agent or connector operations | A scoped quote covers one-time and recurring costs |
| Exit and continuity | Export formats, API limits, retention after termination, and ownership of custom workflows | You can retrieve your data and operate or replace integrations if the platform changes |
Current comparable prices were not established for these platforms. Do not rank them on an invented cost-per-user figure. Request a quote based on your number of projects, users, modules, integrations, data volume, environments, support tier, and expected agent usage.
6. Run a controlled pilot before expanding
A pilot should answer one operational question with real, controlled data. It should not be a general demonstration using curated sample files.
- Select one bounded workflow. Good candidates include finding an approved answer across project documents or turning field observations into a draft report. Choose a task with a measurable start and finish.
- Define success before configuration. Record target accuracy, response time, time saved, exception rate, user-review burden, and auditability. Decide what counts as an unacceptable error.
- Prepare representative data. Use your document structures, naming conventions, revisions, permissions, photos, and field terminology. Remove unnecessary personal or commercially sensitive data.
- Limit permissions. Start read-only where possible. Restrict the agent to one project, folder, model, or record set. Require human approval for every write action.
- Document the integration path. Record the connector or API, fields transferred, transformation rules, trigger cadence, rate limits, retry behavior, and owner responsible for failures.
- Test normal and difficult cases. Include superseded drawings, duplicate filenames, missing metadata, contradictory notes, poor-quality images, offline uploads, and records the user should not be able to see.
- Review every output. Have a qualified project user verify citations, quantities, locations, dates, cost codes, and proposed actions. Log errors rather than silently correcting them.
- Measure the agreed outcomes. Compare the pilot with the current manual process using the same task set. Separate time saved from time spent reviewing or fixing results.
- Make a go, revise, or stop decision. Expand only if accuracy, control, field usability, and ownership meet the thresholds you set. If not, identify whether the problem is data quality, integration scope, model behavior, permissions, or workflow design.
Example pilot: document answer retrieval
Give the agent access to one controlled project’s approved drawings, specifications, RFIs, and submittals. Ask questions that require revision awareness, such as identifying the approved detail for a particular room and citing the document revision. Check whether the answer excludes superseded files, respects folder permissions, and provides evidence a superintendent can inspect. The pilot is successful only when the result is both useful and traceable.
Example pilot: field observation to draft report
Use a limited set of field photos, videos, spoken observations, locations, and cost codes. Have the agent produce a draft report without automatically posting it. A reviewer should verify quantities, locations, trade attribution, and schedule references before any record is created. Track the number of corrections and the time required for review.
7. Test field conditions, not just office connectivity
Construction workflows occur on mobile devices, in noisy areas, with intermittent connectivity and limited time. Test the exact devices and network conditions used by supervisors and crews.
- Record how the workflow behaves when a device is offline or loses connection during upload.
- Check whether photos and videos are compressed, delayed, duplicated, or associated with the wrong location.
- Measure the number of taps and screens required to capture an observation.
- Verify that users can see the source record, agent suggestion, approval control, and final status without switching between impractical applications.
- Test accessibility, language, and role-specific views for the people who will use the workflow.
If the pilot works only in a quiet office with a curated dataset, it has not demonstrated field readiness.
8. Budget implementation and ongoing ownership
The subscription is only one part of the decision. Ask for a scoped quote that separates recurring licenses and modules from one-time implementation work and continuing integration operations.
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Include these cost categories
- Platform licenses and required modules
- API, connector, marketplace, or usage fees
- Data migration, cleansing, and metadata mapping
- Integration design, development, testing, and deployment
- Training, change management, and project administration
- Monitoring, support, credential rotation, and incident response
- Agent usage, storage, compute, or model charges where applicable
- Ongoing maintenance when an API version, connector, or workflow changes
Assign an owner for each integration and agent workflow. “IT” alone is not enough: project controls, finance, safety, field operations, security, and the vendor may each own part of the process.
9. Protect continuity and your exit options
Before signing, determine what happens if the vendor changes an API, retires a preview, alters permissions, or you leave the platform.
- Which records, files, metadata, audit logs, and model relationships can be exported?
- Are exports complete, machine-readable, and available without a professional-services engagement?
- What API limits or retention rules apply after contract termination?
- Who owns custom code, mappings, prompts, evaluation sets, and workflow configurations?
- How much notice is provided for breaking API changes or connector retirement?
- Can a replacement system access the same source data without the agent becoming a proprietary dead end?
Document the answers in the procurement record. A technically impressive agent is a weak investment if your organization cannot retrieve its project history or maintain the workflow independently.
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Choosing the loudest AI announcement
Why it fails: An announcement or roadmap does not establish production availability, permissions, support, or reliability.
Correction: Put every proposed feature in the maturity ladder and count it in the business case only after a documented test in your environment.
Counting integrations instead of checking coverage
Why it fails: A large integration count may include connectors that do not expose the objects, fields, write operations, or cadence your workflow requires.
Correction: Trace one complete data path from source to agent to destination and record every transformation and approval step.
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Why it fails: A broadly privileged identity can expose unrelated projects or make high-impact changes without a clear human owner.
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Correction: Use delegated identity or least-privilege scopes, restrict project boundaries, start read-only, and require approval for writes.
Using only clean demonstration data
Why it fails: Real projects contain superseded revisions, missing metadata, duplicate names, contradictory notes, and poor-quality media.
Correction: Include these failure cases in the pilot and measure exception handling and review time.
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Ignoring maintenance
Why it fails: Connectors, APIs, permissions, and agent behavior change. An integration without an owner will silently degrade.
Correction: Assign operational ownership, define monitoring and alerts, keep test cases, and schedule periodic permission and output reviews.
Assuming a partner directory is a recommendation
Why it fails: Directory inclusion establishes an ecosystem listing, not a fit assessment, availability guarantee, or performance result.
Correction: Evaluate the partner against the same data, security, field, cost, and exit criteria as every other option.
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Select the platform that covers your essential workflows and lets you prove one valuable agent use case with controlled access, observable activity, and a credible operating model. If a platform has attractive agent features but cannot expose the required project data or provide acceptable governance, it is not ready for your use case. If its AI capability is still preview or announced, treat it as an experiment rather than a committed production dependency.
Reconfirm availability, plan limits, regional access, pricing, and API status during procurement. The Procore and Autodesk statements cited above are dated vendor descriptions; both platforms may change the names, scope, and maturity of their agent capabilities after those publication dates.
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