Turn EnterpriseDealsQPAST-CTinto Technical Wins
An AI-powered presales validation platform that transforms discovery, solution architecture, sizing, and competitive positioning into a structured framework that secures the technical approval behind every enterprise deal.
Turn EnterpriseDealsinto Technical Wins
An AI-powered presales validation platform that transforms discovery, solution architecture, sizing, and competitive positioning into a structured framework that secures the technical approval behind every enterprise deal.
The Problem
Enterprise Sales Has a Hidden Weak Point
While sales teams have dozens of tools to manage pipelines, presales remains largely unstructured.
The result?
Over 80% of enterprise deals fail due to poor presales execution.
Weak or generic
solution pitches
Unclear Sizing
Assumptions
Poorly Validated
Architectures
Vague ROI or
TCO justification
The Business Case for Pre-Sales Excellence
Industry research shows the cost of poor pre-sales execution — and the upside of getting it right.
of deals lost had unresolved technical objections at time of close
higher win rate when pre-sales is engaged in the first meeting
reduction in sales cycle when technical conviction is established early
of champions say SE credibility influenced their internal advocacy
The Solution
A Structured Framework for Technical Validation
QPAST-CT introduces a 7-pillar methodology that transforms presales from intuition-based selling into a repeatable technical validation process.
Instead of relying on ad-hoc presentations and gut instinct, teams use a systematic evaluation model that aligns technical solutions directly with business outcomes.
The QPAST-CT
Methodology
A seven-stage validation framework designed for enterprise presales.
Discover real customer priorities using AI-generated discovery questions that uncover pain points, decision criteria, and stakeholder expectations.
Analyze your solution pitch using AI to evaluate delivery, clarity, messaging alignment, and effectiveness.
Map the customer's technical environment and design future-state architecture aligned with their stack and integration points.
Determine the right infrastructure capacity based on expected usage, growth, performance needs, and data volumes.
Build a credible Total Cost of Ownership model that justifies the investment with measurable value.
Analyze competing solutions and clearly position your technical differentiators.
Secure stakeholder approval by validating feasibility, risk factors, and overall technical fit.
Discover real customer priorities using AI-generated discovery questions that uncover pain points, decision criteria, and stakeholder expectations.
Analyze your solution pitch using AI to evaluate delivery, clarity, messaging alignment, and effectiveness.
Map the customer's technical environment and design future-state architecture aligned with their stack and integration points.
Determine the right infrastructure capacity based on expected usage, growth, performance needs, and data volumes.
Build a credible Total Cost of Ownership model that justifies the investment with measurable value.
Analyze competing solutions and clearly position your technical differentiators.
Secure stakeholder approval by validating feasibility, risk factors, and overall technical fit.
Impact on your
Deal Cycle
Based on 20+ years of enterprise presales practice and QPAST-CT framework validation across real deals.
Gut feel & averages
Inconsistent across SEs
30–40% of pipeline lost
at final stages
Extended by unresolved
technical & commercial gaps
~30% of SE effort wasted
on unwinnable deals
±40% miss rate
Based on CRM stage alone
Structured 7-pillar QPAST-CT score
Objective, repeatable, comparable
Risk flagged early at pillar level
Recovery actions triggered in time
Gaps surfaced & closed faster
through structured discovery
Zombie deals identified early
SE effort redirected to wins
Evidence-based confidence score
Linked to Salesforce deal status
Without
Gut feel & averages
Inconsistent across SEs
With PSF
Structured 7-pillar QPAST-CT score
Objective, repeatable, comparable
Without
30–40% of pipeline lost
at final stages
With PSF
Risk flagged early at pillar level
Recovery actions triggered in time
Without
Extended by unresolved
technical & commercial gaps
With PSF
Gaps surfaced & closed faster
through structured discovery
Without
~30% of SE effort wasted
on unwinnable deals
With PSF
Zombie deals identified early
SE effort redirected to wins
Without
±40% miss rate
Based on CRM stage alone
With PSF
Evidence-based confidence score
Linked to Salesforce deal status
Platform Features
AI-Powered Presales Intelligence
QPAST-CT combines enterprise sales methodology with intelligent automation.
Discovery Intelligence
AI generates contextual discovery questions based on company strategy, financial performance, and industry trends.
Pitch Analysis Engine
Upload solution presentations or videos and receive objective feedback on clarity, confidence, and effectiveness.
Sizing & Capacity Planning
Estimate workload demands, performance expectations, and scalability requirements.
TCO & ROI Modeling
Build financial justification models that clearly demonstrate long-term value to decision makers.
Technical Win Scoreboard
Track validation progress and measure deal readiness before entering final approval stages.
Why It
Matters?
Organizations that implement structured presales validation gain:
Secure the Technical Win
Bring structure, intelligence, and repeatability to enterprise presales.