Tailored AI Workflows for ERP & CRM
BusinessForward.AI builds custom document parsing applications that transform unstructured emails, PDFs, notes, and messages into validated, structured records in your internal business software. Unlike raw cloud API tools, our solutions connect unstructured communication directly to ERP, CRM, and project management systems - complete with fuzzy matching and human-in-the-loop approval.
Combine text document parsing with voice AI mobile applications that turn unstructured field speech into clean database entries.
Real-World Workflow Example
Email says: "We need 50 feet of two-inch PVC on job site B."
Intent: Material request
Item: 2-inch PVC
Quantity: 50 feet
Destination: Job Site B
The email parsing application uses fuzzy logic to match "2-inch PVC" with ERP inventory specs (e.g., 2.0" PVC Pipe) and link the request to Job Site B's active project ID.
Application creates a structured JSON payload and sends it to your backend system via API, or saves the record for human-in-the-loop approval before posting.
Unstructured Data to Business Records
AI data extraction workflow: transform unstructured documents, messages, notes, and other business content into validated records for ERP, CRM, project management, inventory, or internal database systems.
The application receives unstructured business information from sources such as emails, digital PDF documents, text messages, field notes, pasted text, or other software-generated content.
The AI engine identifies the purpose of the input and extracts the relevant fields. For example, an informal request such as
Send 50 feet of two-inch PVC to job site B
can be converted to:
Intent: Material request
Item: 2-inch PVC
Quantity: 50 feet
Destination: Job Site B
The application cross-references extracted values against existing business records. Shorthand product descriptions, customer names, project locations, part numbers, and other identifiers can be matched to the correct ERP, CRM, inventory, or project records using entity resolution and fuzzy matching. Ambiguous or low-confidence results can be routed for human review.
Validated information is converted into structured data such as JSON payloads, database records, or other formats required by the destination software.
The resulting records can be sent through APIs or database integrations to ERP, CRM, project management, inventory, accounting, or other internal business systems.
The Result: Unstructured business information becomes clean, validated data that can be reviewed, stored, or entered into existing software without repetitive manual data entry.
One common application of this process is automatically converting incoming emails into backend business records. See AI Email Parsing & Email-to-ERP Automation for a detailed example.
Supported Integrations & Workflows
Input types: Customer and vendor email threads, email attachments, spec sheets, field SMS, chat logs, pasted message text
What can be extracted: Communication type (requirements change, field report, order), PO numbers, project names, delivery dates, job site locations, material description, SKUs, part numbers, quantities
Attachments: Images and document attachments can be added to the record and uploaded to backend software.
SKU Resolution: Reconciles shorthand like "2 in PVC schedule 40" to the exact master SKU PVC-200-S40
Account Mapping: Matches customer names to active ERP account IDs
Job Site Lookup: Links casual site addresses to a project number
Low-confidence matches trigger human approval prior to live entry.
ERP: NetSuite, Epicor, SAP Business One, Microsoft Dynamics 365
Accounting: QuickBooks Online, QuickBooks Enterprise, Sage / Intacct
Construction Project Management: Procore, Autodesk, Buildertrend
Field Service Management: Fieldwire, FieldEquip
Trade Contractors PM: ServiceTitan, Housecall Pro, Jobber, Simpro
Warehouse & Inventory Management: Fishbowl, QR Inventory, Cin7, Odoo
Proven in Production
The core AI / NLP capabilities used in the data extraction applications are already active in production within QR Inventory - our mobile platform for field and warehouse inventory management.
The production software interprets unstructured input, extracts intent and key entities, matches informal descriptions to structured business records using fuzzy logic, and converts the result into actions - delivering data a user asked for, or entering an inventory transactin into QR Inventory cloud backend. These same underlying capabilities form the foundation of our custom document parsing and data extraction applications.
Beyond Keyword Search
Parsing free-form emails, messages, and unstructured documents is more than finding relevant keywords. A production-ready AI application must understand intent, resolve incomplete details, and cross-reference extracted request items against existing ERP or CRM data (such as matching shorthand product names, job sites, or customer accounts).
We build custom parsing logic and validation rules tailored specifically to your operational workflows, legacy databases, and human review preferences.
Data Integrity & Entity Resolution
Real-world emails and messages rarely use exact database part numbers or official account titles. Our AI parsing engine uses advanced entity resolution and fuzzy matching algorithms to bridge the gap between casual human descriptions and rigid software schemas.
AI Data Extraction Q&A
A custom AI data extraction application converts unstructured business information into structured records your software can use. It identifies the purpose of a document or message, extracts relevant fields, validates the information against existing business data, and formats the result for storage, review, or entry into another software system.
BusinessForward applications can process unstructured information from sources such as emails, digital PDF documents, text messages, field notes, pasted text, document attachments, and other business communications. The extracted information can include project details, customer information, part numbers, SKUs, quantities, dates, locations, prices, and other workflow-specific fields.
Extracted text often does not exactly match the names stored in an ERP, CRM, inventory system, or project database. BusinessForward uses entity resolution and fuzzy matching to reconcile shorthand product descriptions, customer names, job-site references, part numbers, and other extracted values with the corresponding records in your existing system. Ambiguous matches can be sent for human review.
Yes. After the extracted information has been validated, it can be formatted as structured data such as a JSON payload or database record and sent to ERP, CRM, project management, inventory, accounting, or other internal software through APIs or database integrations. Workflows can also require human approval before records are entered into a production system.
Connected Capabilities
Start with a real input
Show us the source, the records used to check it, and the action employees take next.
