AI-Augmented Presale Framework
A structured presale process that helps software companies move from a qualified lead to a clear, realistic, and commercially strong proposal.
Process
From qualified lead to proposal, with an optional discovery step whenever the scope needs it.
- 1
Qualified Lead
- 2
Preparation
- 3
Client Call
- 4
Requirements
- help
Discovery needed?
Yes
Run a Product Discovery Workshop first.
No
Move straight to solution and estimate.
- design_services
Product Discovery Workshop (optional)
- 5
Solution and Estimate
- 6
Technical Validation
- 7
Proposal
The framework combines business analysis, technical expertise, historical project data, and AI-assisted preparation. AI accelerates the work, while final requirements, solutions, and estimates remain under human control.
1. Lead Qualification and Preparation
The available lead information is reviewed to understand the initial business need, expected timeline, budget, stakeholders, constraints, and open questions.
AI-assisted tools help organize the available information, identify assumptions, and prepare a focused agenda for the first client call.
2. Requirements Clarification
The first client call focuses on the business problem, expected outcomes, users, existing systems, critical requirements, constraints, SLA expectations, and success criteria.
The result is a structured set of requirements, assumptions, exclusions, dependencies, and unresolved questions.
3. Optional Product Discovery Workshop
A Product Discovery Workshop may be added when the scope is unclear, several solution options exist, or a reliable estimate requires deeper analysis.
Possible outputs include:
- clarified scope and priorities;
- user flows and backlog;
- high-level solution;
- risk register;
- roadmap;
- refined estimate.
4. AI-Augmented Solution and Estimation
AI-assisted tools support requirement analysis, project decomposition, dependency detection, risk identification, and preparation of estimation scenarios.
The estimate covers:
- scope of work;
- timeline and price;
- team configuration;
- assumptions and exclusions;
- dependencies and risks;
- contingency and confidence level.
Every estimate is validated by relevant technical specialists. Depending on project complexity, validation may cover critical areas or the complete decomposition and estimate.
5. Proposal Preparation
The final proposal provides a clear view of:
- project objectives and scope;
- high-level solution;
- deliverables and timeline;
- price and team configuration;
- assumptions, exclusions, and risks;
- change management;
- post-development support;
- project KPIs and reporting.
KPIs are included not only to improve project management, but also to give the client transparency, a sense of control, and confidence in the delivery process.
Additional Business Value
The framework also identifies small, low-effort features outside the core scope that can add meaningful business value.
Selected improvements may be proposed during delivery to demonstrate proactivity, strengthen the client relationship, and build additional trust.
Bring this framework into your presale process
Let's discuss implementing the complete presale framework, adapting it to your existing sales and delivery process, and the details of AI-assisted estimation for your team.