Use this skill when a product firm, consulting firm, system integrator, or federal contractor needs to research a target company or government agency and produce an executive-grade Account Intelligence Report as a formatted .docx file. Handles any industry vertical — Life Sciences, Financial Services, Healthcare, Manufacturing, Energy, Retail, Technology, Federal/Government, and more. Fully automates the pursuit research and document generation process. Includes AI Agentic Solutions vision, IP and Research Opportunity mapping, and high-definition charts and visual dashboards.
インストール
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Use this skill when a product firm, consulting firm, system integrator, or federal contractor needs to research a target company or government agency and produce an executive-grade Account Intelligence Report as a formatted .docx file. Handles any industry vertical — Life Sciences, Financial Services, Healthcare, Manufacturing, Energy, Retail, Technology, Federal/Government, and more. Fully automates the pursuit research and document generation process. Includes AI Agentic Solutions vision, IP and Research Opportunity mapping, and high-definition charts and visual dashboards.
Produce a complete, senior-partner-ready Account Intelligence Report on any target company or government agency. Output is a formatted .docx file with high-definition charts, visual dashboards, AI Agentic Solutions vision, and IP & Research Opportunity mapping — ready for a C-suite meeting. Works for any industry vertical. Works for federal agencies and programs.
INPUTS
Required
TARGET_COMPANY — Full legal name (e.g., "Dexcom, Inc." or "U.S. Department of Veterans Affairs")
YOUR_FIRM — The pursuing firm's name (e.g., "Cognizant" or "Deloitte")
PREPARED_BY — Your name
PREPARED_FOR — Internal stakeholder or leadership name
Optional (provide if known; auto-detect otherwise)
TICKER — Exchange and ticker (e.g., "NASDAQ: DXCM"). Use PRIVATE for private companies. Use FEDERAL for government agencies.
FIRM_CREDENTIALS — 3–5 bullets of your firm's relevant credentials, awards, partnerships, or case studies. If omitted, a placeholder section is written.
INDUSTRY_VERTICAL — One of: Life Sciences (Pharma/Biotech), Life Sciences (Medical Devices), Life Sciences (Genomics/Diagnostics), Financial Services (Banking), Financial Services (Insurance), Retail/Consumer, Manufacturing/Industrial, Energy/Utilities, Technology/Software, Healthcare Providers/Payers, Federal/Government. If omitted, auto-detect from research.
PHASE 0 — VALIDATE INPUTS
Before researching, confirm:
TARGET_COMPANY is the full legal name, not an abbreviation or brand name
If TICKER is not provided, search for it; note "PRIVATE" or "FEDERAL" as applicable
If INDUSTRY_VERTICAL is not provided, determine it in Dimension 1 research and apply the correct playbook from references/vertical-playbooks.md
Federal detection rule: If TARGET_COMPANY contains any of: "Department of," "Agency," "Administration," "Bureau," "Office of," "Command," "Corps of," "U.S. Army," "U.S. Navy," "U.S. Air Force," "U.S. Marine," "CMS," "HHS," "DHS," "DoD," "VA," "GSA," "NASA," "FAA," "SEC," "IRS" — set TICKER = FEDERAL and use the Federal/Government vertical playbook.
PHASE 1 — RESEARCH THE ACCOUNT
Conduct all research before writing a single word of the report. Use multiple targeted web searches. Minimum: 3 searches per dimension, 25 total searches.
Every data point must be classified as one of:
Confirmed — sourced from a press release, official announcement, SEC filing, or job posting naming the specific item
Reported — sourced from reputable trade press or analyst report (cite the publication)
[ASSUMPTION — basis] — estimated, inferred, or unverified — flag inline in orange italic immediately after the value
Never present a guess as a fact. Do not write [ASSUMPTION] for things you have confirmed with a source.
Detailed search query patterns are in references/research-protocol.md.
Dimension 1 — Company Profile
Goal: Establish the factual foundation for every section of the report.
Search for:
Full legal name, HQ address, most recent fiscal year revenue, employee count, FY end date
Core products/services and key customer markets
Most recent earnings release: revenue growth, guidance, CEO commentary
Major strategic announcements in the last 12 months (acquisitions, divestitures, cost programs, reorgs)
Federal adaptation: Replace revenue with total annual budget/appropriations (search congressional budget justifications). Replace FY end with government fiscal year (Oct 1 – Sep 30). Search USASpending.gov for contracting history.
Dimension 2 — Leadership Mapping
Goal: Map every C-suite contact with tenure and background. Tenure determines openness to new vendors.
Search for:
CIO, CEO, CFO, CHRO, Chief Digital Officer, COO, Chief Data Officer by name
Month and year each joined this role — leaders under 18 months have open vendor relationships
Prior 2–3 companies and roles for each — reveals background biases
Any public quotes about strategic or technology priorities
Priority contacts for a technology or consulting pursuit:
CIO or CTO (first door)
CFO (budget owner, cost programs)
CHRO (workforce and HCM systems)
Chief Digital Officer or Chief Data Officer (digital transformation)
Business Unit Presidents (line-of-business budgets)
CEO — later-stage only
Federal adaptation: Map to Agency CIO (required by FITARA), Program Executive Officers (PEOs), Senior Contracting Officers, Program Managers. Check the CIO Council directory and the agency's official leadership page.
Dimension 3 — Strategic Priorities
Goal: Identify what leadership has publicly committed to — these are the fundable initiatives.
Search for:
Investor day presentations and strategy decks
Earnings call transcripts (CEO and CFO commentary)
Annual report / letter to shareholders
Cost reduction or transformation program announcements
Capture 3–5 priorities maximum. For each:
What was publicly committed to (cite the exact source: earnings call date, investor day date, press release date)
Why it creates a technology or consulting services need
Which named executive owns it
Federal adaptation: Search for NDAA provisions (DoD), IT Modernization Plans, Strategic Plans, and President's Management Agenda priorities. Inspector General reports identify known gaps and mandated improvements — these are funded requirements.
Dimension 4 — Technology Signals
Goal: Map the current technology landscape and identify the competitive context (incumbents).
Search for:
Confirmed ERP, CRM, ITSM, HCM, and cloud platforms
Any incumbent managed services or outsourcing partner — this defines the competitive threat
Announced platform migrations or modernization programs
Technology vendor partnership announcements in the last 24 months
Federal adaptation: Search SAM.gov contract awards for the agency. Search FITARA scorecard results. Look for known platform consolidation mandates (Zero Trust Architecture, cloud-first policy, CDM program).
Dimension 5 — Job Posting Intelligence
Goal: Open job postings are the most reliable real-time spending signal available publicly.
Cloud architecture, data engineering, AI/ML (= building capability)
IT Director, VP Technology, CIO, Program Manager (= open leadership = new vendor decisions)
Industry-specific roles (see vertical playbooks)
Signal interpretation:
Job Posting Pattern
What It Means
"Sr. Director, ERP"
Active ERP program, likely $5M+ budget
"Salesforce Administrator (3 openings)"
Salesforce expansion in progress
"AWS Solutions Architect — Migration"
Active cloud migration program
"Program Manager — IT Modernization"
Funded modernization program, needs SI
"Director, Vendor Management"
Evaluating or replacing incumbents
"Data Scientist — 5 openings"
Building internal capability; may need platform
Flag any posting older than 60 days as potentially filled.
Federal adaptation: Search USAJobs.gov for agency postings. Search SAM.gov for active RFIs, RFPs, and Sources Sought notices — these are the federal equivalent of job postings with actual budget attached.
Dimension 6 — News and Press Releases
Goal: Surface events that create technology or consulting needs.
Federal adaptation: Search for GAO reports, OIG reports, congressional testimony, and budget hearing transcripts. These are primary sources for federal priorities and funded mandates.
Dimension 7 — Federal Contract Intelligence (Federal targets only)
Goal: Map the existing vendor landscape, identify recompetes and white space.
Search for:
Active contract vehicles (GWAC, BIC, IDIQ, MAC) in use by the agency
Prime contractors and their task order values on SAM.gov
This dimension is mandatory for all federal targets. Skip for commercial targets.
Dimension 8 — AI Maturity & Agentic Readiness
Goal: Assess the company's current AI posture, active agentic initiatives, and the white space for AI-driven transformation. This informs Section 12 (AI Agentic Solutions Vision) and Section 13 (IP & Research Opportunities).
Search for:
Any announced AI programs, LLM adoptions, or GenAI initiatives (earnings calls, press releases, investor days)
AI/ML job postings — volume and seniority signal investment stage (pilot vs. production scaling)
Research publications, patents, or academic partnerships in AI or data science
Chief AI Officer, VP of AI, or Head of Data Science — appointed or hiring (= funded AI program)
AI platform partnerships (Microsoft Azure OpenAI, AWS Bedrock, Google Vertex, Databricks, Snowflake, Palantir)
Any known agentic workflow deployments (autonomous agents, copilots, RPA + AI, decision automation)
IP filings: recent patents related to data, ML models, or proprietary algorithms
R&D spending as % of revenue (from 10-K, earnings call) — higher % = stronger innovation culture
Academic collaborations, research lab sponsorships, or innovation center announcements
Talent — AI/ML headcount density, data science capability
AI Governance — responsible AI policies, model risk management
Agentic Readiness — workflow automation maturity, API-first architecture, tolerance for autonomous systems
This dimension applies to all targets. Federal agencies: also search for AI Executive Order compliance, AI use case inventories (OMB mandate), and CDO/Chief AI Officer appointments.
PHASE 2 — BUILD THE .DOCX REPORT
After completing all research, generate the report.
Step 2.1 — Apply the Industry Vertical Playbook
If INDUSTRY_VERTICAL was not provided, determine it from research results.
Load references/vertical-playbooks.md and apply the corresponding playbook to:
Calibrate which technology platforms are likely (confirmed vs. inferred)
Identify the right opportunity categories for the Opportunity Map
Set the competitive context (who are the likely incumbents)
Adjust the outreach strategy tone and hook
Step 2.2 — Write the Node.js generation script
Use references/docx-generator.md as the code scaffold. Write a complete Node.js script (generate-report.js) that:
Imports docx (v8.x) and fs
Defines all color constants as specified in the Formatting Reference below
Defines all helper functions (sectionHeader, dataTable, orgChartBox, assumptionFlag)
Defines a data object with all research findings populated
Builds each of the 11 sections in order
Assembles the Document with a cover-page section (no header) and a main section (with headers from page 2)
Saves to /mnt/user-data/outputs/[CompanyName]_Account_Intelligence_[YourFirm].docx
Fill every {{PLACEHOLDER}} in the data object with researched content. Do not leave any placeholder unfilled. If a specific data point could not be confirmed, insert the best estimate and flag it [ASSUMPTION — basis].
3–4 sentences written for a senior partner with 45 seconds. Answer: why this account, why now, what is the single best entry point. Do not list everything — synthesize to the most important insight. No bullet points in this section.
SECTION 2 — Company Snapshot
Single table with rows:
Field
Value
HQ
[address]
Revenue
[most recent FY, with year]
Employees
[count]
Fiscal Year End
[month]
Exchange / Ticker
[e.g., NASDAQ: DXCM or FEDERAL]
Core Products
[brief]
Key Markets
[brief]
Strategic Moment
[one sentence: where is this company right now]
SECTION 3 — Leadership Hierarchy
Part A: Visual Org Chart
Three-tier colored table:
Row 1: CEO box — NAVY background
Row 2: C-Suite boxes — BLUE background (side by side)
Row 3: Business Unit Presidents / VPs — TEAL background (side by side)
Each box contains:
Name (bold, white)
Title (white)
"Since [Month Year]" (small, MUTED)
Mark primary pursuit contact with ★
Mark leaders under 18 months with ⚡ New
Part B: Leadership Table
Name / Title
Background (prior 2–3 roles)
Tenure
Why They Matter to This Pursuit
Part C: Analytical Note
One paragraph assessing leadership stability. Answer: How new is this team? New C-suite = open vendor decisions, relationships not yet locked. Entrenched leadership = incumbent protection required, need a different entry strategy.
SECTION 4 — Strategic Priorities
3–5 priorities maximum, sourced only from public statements.
For each priority:
Priority title (subsection header)
What leadership publicly committed to — cite source (earnings call date, investor day, press release date)
Why it creates a technology or consulting need
Named executive owner
Do not fabricate priorities. Every priority must have a citation.
SECTION 5 — Technology Landscape and Spending Signals
Part A: Incumbent Partners
Name any confirmed managed services or outsourcing partners. These are the competitive context. If an incumbent is confirmed, note the relationship age and any signals of dissatisfaction or expiration.
Part B: Spending Estimates Table
Category
Est. Annual Spend
Key Signal
[YOUR FIRM] Opportunity
All spend estimates must be flagged [ASSUMPTION — basis]. Basis should be: industry benchmark % of revenue, confirmed contract award value, or job posting density.
SECTION 6 — Job Posting Intelligence
Table of confirmed open roles relevant to technology or consulting services:
Role Title
Location
Salary Range (if posted)
What It Signals
After the table, a synthesis paragraph: what do these postings collectively tell you about active spending programs and organizational priorities?
SECTION 7 — Technology Stack
Two-column table — never mix columns:
Confirmed (source cited)
Likely / Inferred [ASSUMPTION — basis]
Confirmed = press release, official announcement, job posting naming the specific platform, or vendor case study.
Inferred = industry norm for this vertical, or signals from job postings that suggest but don't confirm a platform.
SECTION 8 — Opportunity Map
Opportunity
Tier
Timeline
Est. Value
Named Champion
Tier definitions:
Tier 1 — 0–6 months: Active, fundable, champion identified, there is a near-term trigger
Tier 2 — 6–18 months: Likely, but needs relationship development or internal decision to crystallize
Tier 3 — 18+ months: Strategic, requires the account to evolve or a future event to occur
Rules:
Every opportunity must have a named champion. No champion = not actionable, do not include.
All value estimates must be flagged [ASSUMPTION — basis].
Minimum 2 Tier 1 opportunities. If research cannot support 2, explain why in a note below the table.
SECTION 9 — [YOUR FIRM] at a Glance: Why We Win
Two-column table using FIRM_CREDENTIALS:
Credential / Recognition
What It Means in a Client Conversation
For each credential, write 2–3 sentences translating it into relevance for THIS specific account. Do not list awards — explain why they matter here.
If FIRM_CREDENTIALS was not provided: write a placeholder section with this note: "Insert your firm's relevant credentials, analyst recognitions, partnership tiers, and referenceable case studies here before this document is used in a pursuit."
SECTION 10 — [YOUR FIRM] Strategy and Vision for [TARGET COMPANY]
10.1 — Vision Statement
One paragraph in a full-width NAVY box. Written specifically for this account — not a generic firm positioning statement. Answer: what does [YOUR FIRM] want to be for this company, and what makes [YOUR FIRM] the right choice to deliver it?
10.2 — Case Studies to Showcase
Four case studies mapped to THIS account's confirmed priorities. Do not map a healthcare case study to a manufacturing account. Use FIRM_CREDENTIALS if provided. If credentials are thin, write plausible case study types based on the opportunities and flag them [ASSUMPTION — confirm with your firm's BD team before using in a client meeting].
Case Study
Relevance to [Company]
Talking Points
10.3 — Proposals to Build Before First Meeting
Four specific, named proposal concepts. Each requires:
A title that sounds like a real engagement (not "Advisory Services" or "Digital Transformation")
The named champion who would approve it
A 3–5 sentence core argument — the actual pitch
An indicative price range flagged [ASSUMPTION — basis: market rate for scope described]
Proposal Title
Target Champion
Core Argument
SECTION 11 — Recommended Outreach Strategy
Answer all five specifically. No generic advice.
11.1 Who to contact first
Named person, specific title, and the concrete reason they are the right door — not just "they own technology."
11.2 What to lead with
One specific hook: a job posting they have open, a quote from their earnings call, a news event in the last 30 days, a product launch, a regulatory event. One sentence.
11.3 Draft email opening
Write the first 3 sentences of the outreach email. It must reference something specific to THIS person at THIS company — their recent statement, their background, their open challenge. No generic intros.
11.4 Best timing
A specific date window and the reason (post-earnings quiet period ending, pre-budget cycle, 90 days after new leader arrival, pre-contract expiration).
11.5 What NOT to do
One or two pitfalls specific to this account: incumbent relationship to avoid triggering, internal politics to be aware of, messaging that will backfire, regulatory sensitivity.
SECTION 12 — AI Agentic Solutions Vision
This section presents [YOUR FIRM]'s vision for transforming [TARGET COMPANY] through AI and agentic solutions — grounded in the company's confirmed strategic priorities and AI maturity signals from Dimension 8 research. It must be specific to this company's context, not a generic AI pitch.
12.1 — AI Readiness Assessment
A scored evaluation of the company's AI maturity across five dimensions. Present as a color-coded scorecard table with a visual progress indicator for each dimension. Each score (1–5) must be derived from Dimension 8 research signals — not generic.
Dimension
Score (1–5)
Evidence / Signal
Implication
Data Maturity
[1–5]
[Specific signal from research]
[What this means for AI buildout]
Infrastructure Readiness
[1–5]
[Signal]
[Implication]
AI / ML Talent
[1–5]
[Signal]
[Implication]
AI Governance
[1–5]
[Signal]
[Implication]
Agentic Readiness
[1–5]
[Signal]
[Implication]
Generate a visual AI Readiness Radar Chart as a PNG image embedded in the document (using chartjs-node-canvas). The radar plots all five dimensions on a pentagon grid with scores 1–5. Use NAVY fill with 40% opacity and BLUE border.
12.2 — AI Agentic Use Case Roadmap
Map 6–10 specific AI agentic use cases to this company, organized into three tiers based on implementation readiness and business impact. Each use case must tie back to a confirmed strategic priority or identified pain point — not a generic AI capability.
Use Case
Business Function
Strategic Link
Impact
Complexity
Tier
[Specific use case]
[Function]
[Links to Priority X]
[H/M/L]
[H/M/L]
[1/2/3]
Tier definitions for AI use cases:
Tier 1 — Deploy Now (0–6 months): Foundation models available, low data prep required, quick ROI demonstration
Tier 2 — Build This Year (6–18 months): Requires data integration or governance work first; high strategic impact
Generate a visual Priority Matrix Chart (bubble chart) as a PNG image: X-axis = Implementation Complexity, Y-axis = Business Impact, bubble size = estimated value. Color by tier (TEAL = Tier 1, BLUE = Tier 2, NAVY = Tier 3).
12.3 — [YOUR FIRM]'s Agentic Delivery Model for [TARGET COMPANY]
Describe specifically how [YOUR FIRM] would deliver the AI agentic vision — not a generic methodology description. Address:
Which AI platform(s) would anchor the solution (tied to company's confirmed tech stack)
[YOUR FIRM]'s proprietary accelerators, pre-built agents, or AI frameworks relevant to this vertical
Named platform partnerships ([YOUR FIRM] + Microsoft / AWS / Google / Databricks + how it applies here)
The sequencing: what gets built first and why, tied to the Tier 1 use cases above
Governance and responsible AI framework [YOUR FIRM] would put in place for this account
12.4 — AI Investment Framing
Two-column framing table — cost of inaction vs. value of action. All figures must be flagged [ASSUMPTION — basis].
Investment Area
Est. Investment
Est. Annual Value Capture
Payback Period
After the table: a 3–4 sentence narrative on how [YOUR FIRM] would present the AI business case to the CFO of this specific company — referencing their known cost pressures or growth mandate from Section 4.
SECTION 13 — IP & Research Opportunities
This section maps the intellectual property and research innovation landscape for [TARGET COMPANY] and identifies co-innovation opportunities with [YOUR FIRM]. It is forward-looking — the goal is to identify where jointly developed IP or research partnerships could create durable competitive advantage.
13.1 — IP Landscape Assessment
Map the company's current IP posture across three categories. All items must be sourced or explicitly flagged [ASSUMPTION].
IP Category
Current State
Strength
Gap / Opportunity
Patent Portfolio
[Active patents / filing activity / domains]
[H/M/L]
[Where coverage is thin or novel IP could be filed]
Proprietary Data Assets
[What unique data the company generates or holds]
[H/M/L]
[How it could be monetized or protected]
Proprietary Processes / Algorithms
[Any known trade secrets, proprietary models, unique workflows]
[H/M/L]
[What could be formalized, protected, or built on]
Generate a visual IP Strength Snapshot — a horizontal bar chart (PNG image) showing IP strength by category, color-coded by gap severity (TEAL = strong, ORANGE = gap, NAVY = unknown).
13.2 — Research & Innovation Opportunities
Identify 4–6 specific areas where [TARGET COMPANY] could invest in applied research or co-develop novel solutions with [YOUR FIRM]. Each opportunity must tie to a confirmed strategic priority or a vertical-specific innovation trend.
Research Area
Strategic Rationale
Potential Output
[YOUR FIRM] Role
Timeline
[Area]
[Why this matters for this company now]
[Patent / model / platform / published research]
[Lead / Co-develop / Advisory]
[X months]
13.3 — Co-Innovation Model
Describe how [YOUR FIRM] and [TARGET COMPANY] could structure a co-innovation engagement:
Funding model: How costs, IP ownership, and commercialization rights would be split
Governance: Who owns decisions (named roles at both organizations)
IP framework: What each party brings in, what gets created jointly, how new IP is registered
Milestone structure: What the 6-month, 12-month, and 24-month outcomes look like
Present as a structured table followed by a narrative paragraph (3–4 sentences) on why this model is appropriate for THIS specific company's culture and risk tolerance — based on research signals.
13.4 — Pioneering Bets: Where [TARGET COMPANY] Could Lead the Industry
One of the most intriguing forward-looking sections in the report. Identify 2–3 areas where [TARGET COMPANY] has the unique combination of data, domain position, and strategic intent to become an industry-defining innovator — not just an AI adopter.
For each bet:
The thesis: What makes this company uniquely positioned (specific data asset + domain depth + strategic moment)
The innovation: What novel AI capability, product, or process could be built
The competitive moat: Why competitors could not easily replicate this even if they tried
[YOUR FIRM]'s contribution: What specific IP, platform, or expertise [YOUR FIRM] brings to make this possible
Risk: What could prevent this from happening (technology, organizational, regulatory)
Present each bet in a full-width GOLD callout box for visual distinction.
PHASE 3 — QUALITY GATE
Before saving the file, verify every item:
Every estimated figure has an inline [ASSUMPTION — basis] flag — orange italic in the .docx
No leadership names were inferred — all sourced from press releases, official pages, or confirmed news
No AI filler language anywhere: "leverage," "unlock value," "synergies," "best-in-class," "world-class," "cutting-edge," "transformative," "it is important to note," "game-changing"
Cover page has no logo
Page headers from page 2: firm name left-aligned, document title right-aligned, thin blue bottom border
Org chart uses colored table boxes (NAVY for CEO, BLUE for C-suite, TEAL for VPs) — not a text list
Every opportunity in Section 8 has a named champion
The Section 11 draft email opening is specific to the named person — not a template opener
Federal targets: all contract values are sourced from SAM.gov or flagged [ASSUMPTION]
No section is empty — every section has substantive content or a clearly labeled placeholder
Section 12 AI Readiness scores are grounded in Dimension 8 research — not generic
Section 12 AI use cases are mapped to confirmed strategic priorities from Section 4
Section 12 Radar Chart and Priority Matrix Chart are generated as PNG images and embedded
Section 13 IP assessment covers all three categories (patents, data assets, processes)
Section 13 Pioneering Bets are specific to this company's unique position — not generic AI predictions
Section 13 IP Strength Snapshot chart is generated and embedded
Section 5 Spending Allocation chart (pie/donut) is generated and embedded
Section 8 Opportunity Timeline chart is generated and embedded
All four embedded charts render at correct dimensions (width ≤ 500px in the document)
PHASE 4 — OUTPUT SUMMARY
After saving the file, output exactly three bullets to the user:
Entry point: [Named person], [exact title] — [specific reason they are the right first call, not generic]
Time-sensitive opportunity: [Named opportunity] — [why the window exists now: new leader, open recompete, regulatory deadline, post-earnings, contract expiration date]
First outreach: [Recommended date/window] — Lead with: "[one-line specific hook]"
FORMATTING REFERENCE
Color Constants
NAVY = "1B2A4A" — cover background, section header bars
BLUE = "2E5FA3" — C-suite org chart boxes, subsection text
TEAL = "2E8B7A" — VP/BU org chart boxes, Tier 1 AI use cases
WHITE = "FFFFFF" — text on dark backgrounds
LIGHT = "5BA3C9" — cover company name accent
MUTED = "AACCEE" — cover metadata labels, org chart tenure text
ORANGE = "CC6600" — assumption flags: inline, italic; IP gaps
ALT = "EEF3FA" — alternating table row background
GOLD = "B8860B" — Pioneering Bets callout box background (use "FFF8DC" for light gold)
PURPLE = "6B4FA0" — AI governance / research accent
GREEN = "2E7D32" — positive AI readiness scores (4–5)
RED = "C62828" — low AI readiness scores (1–2)
AMBER = "E65100" — mid AI readiness scores (3)
Chart Specifications (embedded PNG images)
All charts are generated using chartjs-node-canvas and embedded via ImageRun. Four charts are required:
Chart
Section
Type
Size (px)
Purpose
Spending Allocation
Section 5
Doughnut
500×400
Visual breakdown of estimated IT spend by category
Opportunity Timeline
Section 8
Horizontal Bar (Gantt-style)
600×300
Visual map of opportunities by tier and timeline
AI Readiness Radar
Section 12
Radar
500×450
Spider chart of 5 AI maturity dimensions scored 1–5
IP Strength Snapshot
Section 13
Horizontal Bar
500×250
Strength rating per IP category, color-coded by gap
