Problem Statement:
People keep changing within an organization - learning curve for each new person. Expertise of different people might be different - creating a gap between expectations and delivery Monotonous tasks can be automated to boost efficiency Solution
AI model built with full context specific context windows to cater to different needs of the organization. Educator modules to train talent to meet the needs of the organization Utility led tool sets to automate specific tasks Problem-Solution Fit
The eventual scope is to perform as an organization wide intelligence to improve efficiency. The early scope for phase one of development will be limited to empowering the Sales Departments. The latter scope for phase two would include integrations with analytics tools & CRMs to further expand the context windows. The positioning of the entire tool would be to supercharge the teams and departments rather than acting as an assistant tool or summarization tool - there’s already Co-pilot and n number of tools for those purposes. The context adaption would be one of the major challenges we would face, each module would be department specific allowing us to have distinct context windows - within departments context buildr playgrounds with templates and tool kits to configure context will be developed.
The scope for the learning modules can start from basic SOP education to guidance on the subject and the organization’s positioning.
I’m not sure about metrics to map the efficiency gains yet, however I assume that this could be mapped though improved productivity scores, faster timelines, lower expectations to delivery gaps etc.
Product Features and Differentiation
AI Model Strengths: What sets your AI apart from existing solutions in handling organizational context? Not sure about this yet, in early development I’m only considering using OpenAI’s chatGPT API to power the early intelligence. However, going forward we’ll either have to develop a custom model trained on specific datasets or powered with multiple existing models. Integration: How does your tool integrate with existing workflows or software (e.g., CRMs, ERPs)? Integrations are out of scope until second phase of the development - the reason being we do-not want to position ourselves as an extension of the employee in the role, empowering them than doing reporting for them. Scalability: How scalable is the model? Can it handle larger enterprises with complex workflows? Is something that needs to be understood with testing as of now in ideation stages, so I’m not fully aware of this. Customization: Are the automation tools customizable to specific organizational processes? Customization will be integral in the automation tools, a notion like playground interfacing will be required to customize the automation tools to fit the organization specific needs. Examples of these tools in the use-case of sales department would be - Proposal Generator, Minutes of Meetings & Summarization, Personalized Product/Service Generator etc. Target Market and Strategy
Target Audience: Which organizational roles or departments (HR, Operations, IT) are your primary users? The primary target audience for the phase 1 of development cycles would be the sales departments. Size of Companies: Are you targeting SMEs, large enterprises, or both? In the early stages SMEs would be the ideal target audience, so we have a cushion to develop scalability as we work with them. Competitive Landscape: Who are your key competitors? How is your approach superior? Any AI assistance tool could be a potential competitor here, although we’re trying to bring differentiation with our positioning as an extension of the employee than an added feature in a reporting/analytics/intelligence tool. Market Opportunity: How large is the market for such a solution, and how do you plan to capture it? I’m not sure about this yet the TAM would be any and every business that has multiple departments for specific roles, however our early positioning would be to specific sets within this market. I am not sure about this in terms of numbers. Monetization and Business Model
Pricing Structure: Is your solution subscription-based, pay-per-use, or free with premium features? Haven’t explored this yet. Customer Acquisition: How do you plan to attract your first customers? Any specific marketing channels or strategies? Early customer base would come through the existing clientele at fastrBuild, a sister concern to this product. Retention Strategy: What measures will you take to ensure continued use by organizations as they scale or change? Retention Strategy would purely be result oriented, if we bring the value that we claim, no organization should have a problem with the intelligence I assume. To address concerns regarding data protection etc, as we grow we’ll set procedures to ensure this protection. Metrics and Validation
Traction: Do you already have any users or companies testing the solution? If so, what are their feedback and initial results? As of now the product is still in development, the BETA version will be tested by Soffit, where-in we’ll try to empower their sales team with this idea. Pilot Programs: Are you running pilot programs to validate your hypothesis? If yes, what have been the learnings? Pilot program would be a Sales Department Boostr app with all features to support the sales teams within an organization. Explore ways to measure productivity, efficiency, and ROI from the solution. Partner with early adopters to gather qualitative and quantitative data. Research CoPilot and similar tools to clearly articulate your differentiators. Conduct bottom-up calculations for SMEs in your initial market. Explore pricing strategies to balance affordability and profitability. Validate Core Value Proposition: Use Soffit and fastrBuild clients to test key features, focusing on usability and measurable improvements. Incorporate feedback from beta testers to refine the product before launch.
Boostr Product Scope
