How consumer brands, wholesale distributors, and manufacturers are modernizing their manual transactions with Knack Systems' Gen AI capabilities
B2B businesses across wholesale & distribution, industrial manufacturing, chemicals, high tech, building materials, and life sciences in North America share a familiar frustration: critical data still moves through manual entry, costing time and inviting error at every step.
Generative AI promises to change that. But most solutions on the market are still theoretical, polished demos that fall apart when they meet real operational complexity.
At Knack, we've spent years in the trenches of B2B operations. We know what quote-to-order workflows actually look like under pressure. We understand customer-specific pricing, product hierarchies, approval chains, and the messy, unstructured ways B2B customers communicate in the real world. Our engineering team don’t build for ideal conditions, they architect for the constraints and edge cases that break every other solution.
Generative AI is a powerful tool. But a tool is only as good as the hands holding it. The real advantage is knowing exactly where and how to apply the technology when the complexity is real.
In this piece, Knack's Kaushik Ganguly walks through how we built a solution that automates the transformation of unstructured data into actionable digital transactions, cutting manual effort by 70–80%.
Facing manual data entry challenges? Connect with our experts to know the latest industry AI solutions.
The Hidden Cost of Manual Data Entry in B2B Operations
Through our work with enterprise clients, we've identified a critical pain point that affects countless B2B businesses. When customers submit quotes and orders through emails, PDFs, spreadsheets, or even handwritten notes and images, someone on the customer service or sales team must manually transcribe this information into the company's business system.
This manual process creates several compounding problems:
Time Inefficiency
Each quote or order requires 10-30 minutes of manual data entry, depending on complexity. For businesses processing hundreds of requests daily, this translates to significant labor costs.
Processing Bottlenecks
Manual entry limits how many quotes and orders can be processed through existing business systems, creating artificial capacity constraints.
Error Rates
Human transcription inevitably introduces errors—misread numbers, incorrect product codes, or transposed quantities—leading to costly mistakes and customer dissatisfaction.
Lower Conversion Rates
When teams are overwhelmed with manual entry, response times suffer. Delayed quotes mean lost opportunities and reduced conversion rates.
Employee Satisfaction
Talented sales and customer service professionals spend their time on repetitive data entry instead of high-value customer interactions and relationship building.
How Generative AI Solves the Unstructured Data Challenge
Generative AI, particularly multi-modal large language models (LLMs), offers a transformative solution to this problem. Based on our development work and testing, here's how the technology addresses each challenge:
Multi-Modal Understanding
Modern LLMs can process and understand multiple input formats simultaneously—text from emails, structured data from spreadsheets, information from PDF documents, and even handwritten notes captured in images. This multi-modal capability means the same AI system can handle whatever format your customers prefer to use.
Intelligent Data Extraction
Through advanced natural language processing and computer vision, Gen AI can identify and extract relevant information such as product codes, quantities, specifications, delivery addresses, and pricing—even when this information is presented in non-standard formats or handwritten.
Retrieval-Augmented Generation (RAG)
By integrating RAG tooling, the AI system can reference your existing product catalogs, pricing databases, and business rules to validate and enrich the extracted data. This ensures accuracy and consistency with your business systems.
Structured Output Generation
The AI converts unstructured input into clean, structured data formats (typically JSON) that can be directly consumed by your ERP, CRM, or order management systems. This eliminates the need for manual reformatting and ensures compatibility with existing business workflows.
Real-World Impact
At Knack, we developed an implementation system to validate this approach with one of our clients. The results exceeded our initial expectations:
70-80% Reduction in Manual Effort
Tasks that previously required 15-20 minutes of manual data entry now take 3-4 minutes of AI-assisted review and validation. This efficiency gain frees up team members for more strategic work.
Dramatic Increase in Processing Capacity
With the same team size, our client can now process 4-5 times more quotes and orders through their business system. This removes the bottleneck that was limiting their ability to respond to customer inquiries and capture new business.
Improved Conversion Rates
Faster processing times mean quicker responses to customers. Our client reported a measurable improvement in quote-to-order conversion rates as they were able to respond to inquiries within hours instead of days.
Handling Diverse Manual Inputs
The solution handles even the input formats that previously seemed impossible to automate, including those that would traditionally require manual interpretation. What used to be the most time-consuming and error-prone part of the workflow is now processed with the same efficiency as structured data.
Why This Gen AI Transformation Matters for Your B2B Business
Based on our experience implementing this solution and observing its impact, we believe this technology represents a fundamental shift in how B2B businesses can operate:
Competitive Advantage Through Speed
In competitive B2B markets, the first company to respond to an inquiry often wins the business. Automating data entry means your sales team can generate quotes faster than competitors still relying on manual processes.
Scalability Without Proportional Cost Increases
Traditional scaling requires hiring more data entry staff. With AI automation, you can handle significantly increased quote and order volume without proportionally increasing headcount, improving your operational margins.
Better Resource Allocation
Your customer service and sales teams can focus on what they do best: understanding customer needs, providing expert guidance, building relationships, and closing deals—rather than typing data into forms.
Improved Accuracy and Consistency
AI systems, when properly configured with validation rules and RAG integration, can achieve higher accuracy rates than manual data entry, especially for repetitive tasks. This reduces costly errors and rework.
Future-Proofing Your Operations
As Gen AI technology continues to improve, early adopters will benefit from increasingly sophisticated capabilities. The infrastructure you build today will become more powerful over time without requiring fundamental architectural changes.
Manual Entry vs Gen AI vs Traditional RPA
| Approach | Setup Time | Handles Unstructured Data | Accuracy | Scalability |
|---|---|---|---|---|
| Manual Entry | Immediate | Yes | 85-92% | Limited by headcount |
| Gen AI (Knack) | 4-8 weeks | Yes | 99%+ with review | Scales infinitely |
| Traditional RPA | 3-6 months | No | 95%+ (structured only) | Brittle, breaks with changes |
Key Considerations for Successful Implementation
Through our development process, we learned several important lessons that are worth sharing:
Start with a Focused Use Case
Rather than attempting to automate all processes at once, identify your highest-volume, most standardized workflow. Success with one use case builds confidence and provides a foundation for expansion.
Maintain Human Oversight
We recommend an AI-assisted workflow where the system generates structured data but a human reviews and approves before final submission. This catches edge cases while still capturing most of the efficiency gains.
Integrate with Existing Systems
The goal is to enhance your current business systems, not replace them. Ensure your AI solution outputs data in formats that integrate seamlessly with your ERP, CRM, or order management platform.
Plan for Change Management
Your team's workflow will change significantly. Invest time in training, gather feedback, and iterate on the process to ensure adoption and maximize the benefits.
Measure and Optimize
Track metrics like processing time, accuracy rates, conversion rates, and team satisfaction. Use this data to continuously refine your AI models and workflows.
About Knack
Knack develops enterprise software solutions that help B2B companies modernize their operations through intelligent automation. Our team combines deep expertise in business systems integration with cutting-edge AI capabilities to solve real-world operational challenges.
Our AI-powered data transformation is currently delivering impressive results to select clients in the construction, fabrication, and field services industries. We work closely with businesses to understand their unique workflows and develop tailored solutions that integrate seamlessly with existing systems.
Interested in Learning More?
If your business struggles with manual data entry for quotes and orders, we'd love to discuss how Gen AI automation could transform your operations. Our team can provide:
-
A consultation to assess your current workflow and identify automation opportunities
- Demonstrations of our implementation system processing real-world data
- ROI analysis showing potential time savings and efficiency gains for your specific situation
- A roadmap for implementing AI-powered automation in your business
Contact us to schedule a conversation about transforming your unstructured data into digital transactions.
