Finalist · Dempsey Startup Competition 2026
ResolveIQ
Transforming Incident Resolution into Institutional Knowledge
ResolveIQ is an enterprise AI product concept designed to help organizations stop repeatedly solving the same incidents. It captures knowledge generated during incident resolution, turns that context into structured organizational knowledge, and helps teams surface relevant answers when similar problems occur again.
Venture case-model estimates & competition outcomes
$4.8M+
Modeled annual cost of lost knowledge
12.5 hrs
Weekly engineering capacity saved per team
3–5 weeks
Average ramp time modeled as disconnected tools
Finalist
Dempsey Startup Competition 2026
01 · The Problem
Every incident is a lesson nobody learns
Enterprise teams may successfully resolve an outage, but the reasoning behind that resolution is often scattered across tickets, chat conversations, calls, individual expertise, and disconnected knowledge systems.
The immediate operational problem gets fixed. The organizational learning often does not. When a similar incident appears months later, another engineer may have to investigate the same symptoms, reconstruct the same context, and rediscover a solution the organization already knew.
Core Product Insight
The problem is not simply incident resolution. It is organizational memory.
02 · Quantifying the Enterprise Problem
Lost knowledge creates measurable operational drag
The venture model estimated more than $4.8M in annual lost- knowledge costs for a 1,000-person company in a regulated industry. The model grouped that exposure across duplicated investigation, repeat incidents, slower ramp-up, escalation, and compliance and audit risk.
Repeated Investigation
Engineers spend time rediscovering information the organization may already possess.
Knowledge Walks Out
Critical operational context can disappear when experienced employees change roles or leave.
Fragmented Systems
Tickets, chats, meetings, runbooks, and knowledge bases preserve pieces of the incident rather than the complete reasoning.
03 · The Solution
Capture knowledge before it disappears
ResolveIQ was designed around two complementary product experiences: surface existing institutional knowledge before an investigation begins, then capture new knowledge automatically as teams resolve incidents.
ContextWeave™
Answers before investigation begins
When a ticket opens, ContextWeave™ evaluates existing knowledge, scores relevant articles, and surfaces the most useful answer directly in the engineer's workflow.
WarRoom Capture™
Turn incident conversations into knowledge
WarRoom Capture™ converts incident-resolution context into a structured knowledge draft containing root cause, resolution, and prevention guidance for human review before publishing.
Product Blueprint The ResolveIQ product blueprint connects knowledge retrieval, incident-context capture, AI-assisted documentation, human review, enterprise security, and knowledge reuse into one workflow. ResolveIQ venture and product blueprint · Dempsey Startup Competition 2026From incident resolution to institutional knowledge
Incident → Resolution → Reusable Knowledge
01
Incident Opens
Operational context begins accumulating across the team's existing collaboration tools.
02
AI Captures Context
ResolveIQ organizes the incident context and resolution knowledge.
03
Human Reviews
An engineer validates the generated knowledge before publication.
04
Knowledge Reused
Relevant organizational knowledge can surface when similar incidents occur again.
05 · Responsible Enterprise AI
Automation with human accountability
ResolveIQ was designed so AI-generated knowledge does not automatically become organizational truth. Human review remains part of the publishing workflow, allowing an engineer to validate the generated article before it enters the knowledge base.
PII Protection
The product concept includes stripping personally identifiable information as part of secure-by-design processing.
Human Review
An engineer reviews generated knowledge before every publish.
Enterprise Security
The venture design incorporates enterprise security and SOC 2 readiness as product requirements.
06 · Interactive Product Experience
Experience the knowledge gap
The interactive presentation demo places the viewer inside an incident scenario and demonstrates the friction of finding the right resolution context when knowledge is fragmented.
Launch Interactive Demo ↗07 · Business Model
Enterprise SaaS aligned to productivity value
The venture pricing model was designed around employee count and the productivity value of reducing repeated investigation and knowledge loss.
Growth
800 employees
$3,750 / month
Target Buyer
Mid-market enterprise
500–2,000 employees
Modeled ROI
Productivity-based case
6.7×
Pricing and ROI figures shown here are venture-model assumptions, not realized customer results.
08 · Competitive Strategy
Designed for the knowledge created between systems
The competitive thesis was that incumbent tools primarily capture pieces of the incident lifecycle: tickets, documentation, collaboration, search, or service management. ResolveIQ was positioned around the unstructured, multi-channel context created while engineers actually diagnose and resolve an incident.
Incumbents live inside the ticket. ResolveIQ lives in the chaos.
09 · Go-to-Market
Start with regulated enterprises where knowledge loss is expensive
Stage 1 · Pilot
Paid pilots with VP IT Operations at insurance firms, sourced through executive networks.
Stage 2 · Prove Value
Convert successful pilots into annual contracts after demonstrating measurable operational value.
Stage 3 · Expand
Use customer success and expansion to build repeatable enterprise growth.
10 · Venture Validation
From enterprise problem to investor pitch
ResolveIQ advanced as a finalist in the 2026 Dempsey Startup Competition, where the team presented the venture during investor pitch rounds. The venture materials also documented market conversations, an interactive product demo, and user-impact feedback as early validation signals.
Finalist
Dempsey Startup Competition 2026
Interactive Demo
Product experience developed for venture validation
Enterprise Discovery
Market conversations used to test the problem and value proposition
11 · What I Demonstrated
Connecting AI product thinking with enterprise value
AI Product Strategy
Translated an enterprise knowledge-management problem into a focused AI product concept.
Enterprise Workflows
Connected incident response, collaboration, knowledge capture, review, and reuse into one product workflow.
Human-in-the-Loop AI
Designed human validation into the AI publishing process rather than treating generation as organizational truth.
Business Modeling
Connected productivity loss, pricing, ROI, buyer definition, and expansion strategy.
Competitive Strategy
Positioned the product around unstructured incident context rather than duplicating existing ticketing and knowledge tools.
Venture Communication
Translated a complex enterprise AI concept into an interactive demonstration and investor-facing narrative.
Project note: ResolveIQ was developed as a student venture and presented in the Dempsey Startup Competition 2026. Financial impact, pricing, ROI, market sizing, and productivity figures shown in this case study are venture-model assumptions and estimates unless explicitly identified as observed traction. They should not be interpreted as realized customer results.