Cut Call Triage Time with Voice AI for Construction
Voice AI transcribes inbound construction calls in real time. It extracts job details, customer info, and urgency to create instant service tickets.
Syntora specializes in developing custom Voice AI solutions to improve inbound call handling for the construction industry. These systems can transcribe calls in real time and extract critical job details, automating the creation of service tickets. Syntora focuses on architectural clarity and integration with existing client systems, offering a clear path to automating administrative tasks.
This approach would replace the need for an admin to manually listen to voicemails or live calls and type information into a separate project management system. Syntora develops custom AI solutions for organizations that need to automate information extraction from unstructured data. A typical engagement for this type of system involves several weeks of architectural design, development, and integration, tailored to your specific operational workflows and existing software.
What Problem Does This Solve?
Most construction offices rely on standard VoIP systems like RingCentral. They record calls and offer basic transcription, but the output is an unstructured wall of text. A dispatcher still has to read the entire transcript, identify the key details, and manually type them into a job management tool like Procore or Buildertrend. This manual data entry is slow and prone to error.
Some teams try off-the-shelf phone bots from platforms like Talkdesk. These tools are built for e-commerce, not construction. They fail when a caller uses industry terms like 'punch list,' 'change order,' or a specific material name. Their integrations are generic, connecting to Zendesk or Salesforce, but not to the construction-specific software your team actually uses.
Imagine a project manager calls about a material shortage for a specific job site. The call goes to a shared office line. An admin listens to the 3-minute voicemail, writes down the details, looks up the project ID in your system, and then creates a ticket. That single call takes 6 minutes of work. At 50 calls per day, one person spends over 5 hours just on data entry, and critical requests can sit unanswered for hours.
How Would Syntora Approach This?
Syntora would approach this problem by first integrating with your existing telecommunications infrastructure, routing your inbound phone number through a service like Twilio. A webhook would then send the live audio stream of every call to a dedicated AWS Lambda function. Inside this function, we would use a real-time transcription service, such as AssemblyAI, to generate a live transcript with speaker labels. This initial transcription typically processes audio with minimal latency.
As the transcript is generated, it would be streamed to the Claude API. Syntora would engineer a custom prompt to act as an expert construction dispatcher, guiding the model to extract specific entities from the conversation. These entities would include caller name, callback number, job site address, project ID, urgency level, and a concise summary of the call's purpose. Claude returns this information as a structured JSON object, a format we have found more reliable for specific data extraction than generic methods. We have experience building similar document processing pipelines using the Claude API for financial documents, and the same pattern applies to construction-related calls and their associated information.
The Lambda function would then take this structured JSON data. Using an asynchronous requests library like httpx, it would make a direct API call to your existing construction management software, whether it's Procore, Buildertrend, or a specialty CRM like AccuLynx. A new service ticket would be created with all extracted fields pre-populated. The full call transcript and a link to the audio recording would be attached as a note. The objective is to automate ticket creation immediately following the call.
Syntora would build the system with structured logging using libraries like structlog, with logs sent to AWS CloudWatch for monitoring. We would configure alerts that trigger if the function encounters repeated errors or if the Claude API latency exceeds defined thresholds. The deployed system would run within your own AWS account, with typical operational costs for this architecture being low, often under $40/month for up to 1,500 calls. As a deliverable, you would receive the full Python source code for the custom components, ensuring transparency and long-term ownership. The client would be responsible for providing API access credentials for their existing phone system and construction management software.
What Are the Key Benefits?
From Call to Ticket in 8 Seconds
Stop manual data entry. An incoming call is transcribed, summarized, and filed in your project management tool before your dispatcher even hangs up.
No Per-Seat Fees, Just Usage
Pay a one-time build fee. Hosting on AWS costs pennies per call, not a monthly software subscription that grows with your team size.
You Own the Code and the AI Prompt
We deliver the complete Python source code and the exact Claude prompt to your GitHub repository. You can modify or extend it without us.
Alerts for API Failures, Not Voicemails
We use AWS CloudWatch to monitor system health. You get an alert if the transcription API is down, so a human can step in immediately.
Connects Directly to Your PM Software
Native API integration with Procore, Buildertrend, and AccuLynx. Data lands where your team already works, no new software for them to learn.
What Does the Process Look Like?
Week 1: System & Workflow Audit
You provide read-only access to your phone system and project management software. We map your current call handling process and identify API endpoints for integration.
Week 2: Core AI Build
We build the transcription and data extraction pipeline using AWS Lambda and the Claude API. You receive a demo processing 5 of your sample call recordings.
Week 3: Integration & Deployment
We connect the AI pipeline to your live phone number and project management tool. The system goes live for a small group of users for real-world testing.
Weeks 4-6: Monitoring & Handoff
We monitor performance for two weeks, tuning the AI prompt based on live calls. You receive the full source code, a technical runbook, and system documentation.
Frequently Asked Questions
- What factors determine the cost and timeline for this system?
- The primary factors are the number of distinct call types (e.g., warranty vs. scheduling) and the quality of your project management software's API. A system for one call type connecting to a modern platform like Procore takes about two weeks. Supporting multiple complex call types or integrating with a legacy system can extend the timeline to four weeks. Pricing is fixed based on this defined scope.
- What happens if the AI misunderstands a call or fails to create a ticket?
- Every call that fails processing is automatically flagged. The original audio, transcript, and error log are sent to a designated 'human review' email inbox. This ensures no call is ever lost. The system is designed to fail gracefully, defaulting to a manual fallback process so a human can take over within minutes of the error.
- How is this different from using a virtual receptionist service like Ruby?
- Virtual receptionists are humans following a script. They handle simple appointment booking but struggle with complex, construction-specific issues and cannot create tickets directly in your PM software. Our system is an automation layer, not a human replacement. It structures the data from every call so your own expert team can act on it much faster.
- How accurate is the transcription and data extraction?
- Transcription accuracy for clear calls is over 98%. The Claude 3 Opus model correctly extracts structured data over 95% of the time after we tune the prompt on 20-30 of your specific call examples. We target a 99% success rate for critical fields like callback number and job address before we consider the project complete.
- Can it handle different accents or callers speaking Spanish?
- Yes. The underlying transcription models are trained on thousands of hours of diverse audio. The system can be configured for multilingual support, typically handling English and Spanish. We test its performance on your actual call recordings during the build to ensure it works for your specific customer base before the system goes live.
- Who has access to our call data?
- The entire system is deployed on your own AWS infrastructure, so you own and control all data. Syntora only has access during the initial build and monitoring period via temporary, scoped IAM credentials, which you can revoke at any time. The AI models we use from AWS and Anthropic do not train on your API data by default.
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