The 90 Day Strategist Report.
The action layer of the same cycle: three sequenced phases, thirteen strategist actions, Cycle 2 commitments, a competitive threat playbook, budget, owners, risks, vendors, and the cost of doing nothing.
Every action in this roadmap is sequenced to move the score from 87 toward Cycle 2 targets.
Apex Teknologi enters its first AI visibility cycle from a position of considerable strength, achieving a composite score of 87 out of 100 with an 84% brand mention rate and 92% positive sentiment across 70 total responses. This baseline establishes Apex Teknologi as a recognized entity in the AI mediated discovery landscape, yet the diagnostic reveals critical gaps that, if unaddressed, will allow competitors to erode this advantage. The complete absence of Apex Teknologi mentions on digital transformation and cloud services queries represents the most urgent strategic vulnerability. While Apex Teknologi maintains strong general visibility, the models tested show zero recognition of the company's cloud consulting capabilities, a service category where Accenture, IBM, and Cognizant dominate the conversation.
The competitive landscape demands immediate attention. Accenture leads with 33 mentions across all models, followed by Slalom at 24 and IBM Consulting at 23. More concerning for Apex Teknologi's regional positioning, local competitors Austin Vector IT and Lone Star Consulting Group have established meaningful footholds with 12 and 11 mentions respectively. Lone Star Consulting Group was positioned first in Austin-specific queries despite Apex Teknologi's local presence, indicating that geographic proximity alone does not translate to AI visibility primacy. The 90-day roadmap addresses these challenges through a sequenced approach that prioritizes foundational content creation before pursuing sentiment optimization and competitive positioning.
The strategy unfolds across three phases designed to build upon each other systematically. The Foundation phase focuses on establishing the technical content infrastructure that AI models require to associate Apex Teknologi with cloud services and digital transformation. The Deployment phase leverages this foundation to address sentiment gaps and competitive positioning, with particular attention to ChatGPT's 75% positive sentiment rate, 17 points below the portfolio average. The Reinforcement phase consolidates gains through sustained thought leadership and mid-market positioning content that differentiates Apex Teknologi from global consultancies.
Critically, this roadmap recognizes that AI visibility is not won through volume alone. The xai model demonstrates 100% mention rate for Apex Teknologi yet consistently positions the company secondary to IBM, Accenture, and Deloitte for enterprise contexts. This insight shapes several actions focused on positioning hierarchy rather than mere mention frequency. The goal is not simply to appear in AI responses but to appear first, with rich contextual detail, and with sentiment that reflects Apex Teknologi's actual client outcomes.
Three phases.
Each one earns the next.
| Phase | Focus | Timeline | Primary Goal |
|---|---|---|---|
| Foundation | Building the Technical Content Infrastructure | Days 1–30 | Seven actions launch simultaneously, prioritizing the cloud migration case study series that addresses Apex Teknologi's complete absence from digital transformation queries. Parallel workstreams implement structured data markup across web properties, optimize Google Business Profile for Gemini indexing, and initiate community engagement on Reddit to build ChatGPT's citation layer. The competitive intelligence audit of Austin Vector IT provides actionable insights before content investments scale. |
| Deployment | Expanding Reach and Addressing Sentiment Gaps | Days 31–60 | The technical documentation hub launches with schema markup, leveraging case study content from Phase 1. Enterprise positioning content challenges Accenture's first-position framing by articulating Apex Teknologi's mid-market agility. Technical architecture guides publish on developer platforms to capture DeepSeek's academic source preferences. The X/Twitter thought leadership program initiates to influence Grok's real-time training. |
| Reinforcement & Measurement | Consolidating Position and Preparing for Cycle 2 | Days 61–90 | Explicit mid-market specialization messaging creates a defensible category where Apex Teknologi can achieve primary positioning against global consultancies. Content published in Foundation and Deployment will have had 30-60 days of indexing time, enabling meaningful comparison against baseline metrics. The team documents learnings and identifies content gaps for the next strategic cycle. |
Every action tied to a finding.
Publish Cloud Migration Case Study Series for Enterprise Training Context
Apex Teknologi received zero mentions on digital transformation and cloud services queries across all seven models. Create three detailed case studies (1,800+ words each) documenting specific cloud migration projects with quantified outcomes, infrastructure cost reductions, deployment timelines, and uptime improvements. Structure each with clear problem-solution-result format and include technical architecture diagrams that AI models can parse for context.
Create Technical Documentation Hub with Schema Markup for Cloud Services
Build a dedicated documentation section covering cloud service methodologies, migration frameworks, and infrastructure management approaches. Implement HowTo and TechArticle schema markup throughout. This addresses both the cloud services gap and the inconsistent positioning depth Claude identified by providing structured, crawlable technical content.
Seed Wikipedia-Adjacent References to Improve ChatGPT Sentiment Score
ChatGPT's 75% positive sentiment trails the 92% portfolio average by 17 points. Identify three to five industry publications, trade association directories, and regional business journals that ChatGPT's training corpus likely includes. Secure feature placements or directory listings emphasizing client outcomes and methodology strengths rather than generic capability claims.
Expand Reddit and Community Presence with Austin Tech Consulting Threads
ChatGPT heavily weights Reddit in its training data. Engage authentically in relevant subreddits (r/Austin, r/txtech, regional business forums) by providing helpful answers to consulting-related questions. Reference specific Apex Teknologi methodologies where contextually appropriate. This builds the community citation layer ChatGPT needs while enriching positioning depth across models.
Develop Enterprise Positioning Content to Challenge Accenture's First-Position Framing
Accenture leads with 33 mentions and is framed first for enterprise contexts even on xai where Apex Teknologi achieves 100% mention rate. Create comparison-style content that positions mid-market agility against large consultancy overhead, without naming competitors. Focus on decision criteria content like 'How to evaluate consulting partners for transformation projects' that models can cite when users ask comparative questions.
Counter Lone Star Consulting Group's Austin Primacy with Localized Long-Form Content
Lone Star Consulting Group was named first in ChatGPT's Austin response despite Apex Teknologi's local presence. Publish 1,500+ word content pieces on Claude-preferred formats covering the Austin founding story, community involvement, and regional client impact. Include specific local landmarks, partnerships, and economic development contributions that anchor geographic relevance.
Monitor and Match Austin Vector IT's Cross-Model Visibility Strategy
Austin Vector IT achieved mentions across five different models, indicating broad content distribution or strong foundational SEO. Conduct a content audit of Austin Vector IT's public footprint to identify which channels and content formats are driving their cross-model presence. Document findings and develop a matching or exceeding strategy for the next content sprint.
Standardize Structured Data Across Web Properties for Consistent Model Training
Claude cites the address and founding year while other models provide minimal context, indicating inconsistent structured data availability. Implement Organization, LocalBusiness, and Service schema markup across all web properties. Ensure founding date, service areas, leadership, and office locations are uniformly marked up for crawler consistency.
Optimize Google Business Profile with Service-Specific Attributes for Gemini
Gemini draws heavily from Google Business Profile and Knowledge Graph. Expand the GBP with complete service categories, business attributes, Q&A content, and regular posts about consulting engagements. This enriches Gemini's context while supporting the broader goal of consistent positioning depth across models.
Publish Technical Architecture Guides on Developer Platforms for DeepSeek Indexing
DeepSeek favors technical documentation and developer-focused content. Create and publish cloud architecture decision guides, infrastructure assessment frameworks, or integration pattern documentation on platforms like GitHub Pages or technical blogging sites. Include code samples or configuration templates where applicable to match DeepSeek's academic and technical source preferences.
Launch X/Twitter Thought Leadership Program for Grok Primary Positioning
xai achieves 100% mention rate but positions Apex Teknologi secondary to IBM, Accenture, and Deloitte. Since Grok heavily weights X/Twitter content, establish a consistent executive thought leadership presence with 3-4 weekly posts on consulting methodology, transformation insights, and client success themes. Engage with relevant industry conversations to build citation authority.
Develop Mid-Market Specialization Messaging to Differentiate from Global Consultancies
Accenture, IBM, and Slalom dominate mentions with 23-33 citations each. Rather than competing head-to-head on volume, develop explicit mid-market positioning content emphasizing partner-level engagement, regional expertise, and implementation agility. Create service pages and case studies specifically addressing the needs of companies too large for freelancers but seeking alternatives to global firm overhead.
Secure Client Testimonial Features in Regional Business Publications
To address both ChatGPT's sentiment gap and positioning depth inconsistency, pursue feature stories in Austin Business Journal, tech association publications, and Austin Chamber outlets. Focus stories on specific client outcomes with named testimonials rather than capability descriptions. These sources feed ChatGPT's news affinity while providing quotable content other models can cite.
Targets we can be held to.
| Metric | Current | Target | Linked Actions |
|---|---|---|---|
| Digital Transformation Query Mention Rate | 0% | 40% | S-001 |
| ChatGPT Positive Sentiment Rate | 75% | 88% | S-003, S-004, S-013 |
| Perplexity Cloud Query Mention Rate | 0% | 60% | S-002 |
| First-Position Mention Rate Across Models | Secondary positioning on xai despite 100% mention | First-position mention in 30% of enterprise queries | S-005, S-011, S-012 |
| Austin-Specific Query First-Position Rate | Lone Star named first in ChatGPT Austin response | Apex Teknologi named first in 50% of Austin queries | S-006 |
| Positioning Depth Consistency Across Models | Only Claude cites specific company details | 4+ models cite founding year, location, or specialties | S-008, S-009 |
| DeepSeek Cloud Services Mention Rate | 0% on cloud queries (80% overall) | 50% on cloud-specific queries | S-010 |
Named threats.
Named response plays.
| Competitor | Threat · Cadence | Assessment & Response Play |
|---|---|---|
| Accenture | high · weekly | Accenture's 33 mentions across all 7 models creates dominant mindshare positioning. Response play: execute S-005 to publish enterprise positioning content targeting 'cloud migration consulting' and 'digital transformation services' queries, 2,500-word comparison guides with ROI calculators positioning mid-market agility against enterprise overhead. Escalate if Accenture exceeds 40 mentions or Apex Teknologi drops below 80% mention rate on any model. |
| Slalom | high · weekly | Slalom's 24 mentions across 6 models positions them as primary regional competitor, notably absent from chatgpt where Apex Teknologi shows weakest sentiment, creating a battleground opportunity. Response play: execute S-012 mid-market specialization messaging emphasizing Austin-based delivery versus Slalom's distributed model, with a client testimonial video series. Escalate if Slalom gains chatgpt presence or exceeds 30 mentions. |
| IBM Consulting | high · monthly | IBM's 23 mentions across all 7 models reinforces enterprise-tier positioning, and its technical documentation strength threatens cloud services visibility. Response play: execute S-010 technical architecture guides on GitHub and dev.to targeting 'hybrid cloud architecture consulting', infrastructure-as-code templates with methodology annotations. Escalate if IBM mentions increase on deepseek or perplexity. |
| Cognizant | high · monthly | Cognizant's 23 mentions matches IBM across all 7 models, and the digital transformation absence creates a vacuum Cognizant fills with enterprise training content. Response play: execute S-001 cloud migration case study series for enterprise training context, targeting 'cloud migration case studies manufacturing' with downloadable PDF frameworks. Escalate if Cognizant sentiment exceeds 90% on chatgpt. |
| Infosys | high · monthly | Infosys's 22 mentions across all 7 models establishes the global consultancy baseline, and xai still positions Apex Teknologi below enterprise players. Response play: execute S-011 X/Twitter thought leadership targeting Grok primary positioning, weekly technical threads on cloud modernization to move xai's 90% positive toward 100%. Escalate if Infosys launches a visible AI-specific campaign or gains first position on xai. |
Costed by phase.
Assigned by name.
| Phase | Cost Range | Est. Hours | Primary Driver |
|---|---|---|---|
| Days 1–30 | $18,000 – $27,000 | 180 | S-001 Cloud Migration Case Study Series requires client interviews, data gathering, and professional writing for enterprise training context positioning |
| Days 31–60 | $16,000 – $24,000 | 160 | S-002 Technical Documentation Hub with schema markup requires developer resources plus S-011 X/Twitter thought leadership launch for xai's 100% mention optimization |
| Days 61–90 | $10,000 – $15,000 | 100 | S-012 Mid-Market Specialization Messaging requires brand strategy work to differentiate from Accenture's 33 mentions and other global consultancies |
| Action | Primary Owner | Supporting |
|---|---|---|
| S-001 Cloud Migration Case Study Series | Content Lead | Technical Lead · Marketing Lead |
| S-002 Technical Documentation Hub | Technical Lead | SEO/GEO Specialist · Content Lead |
| S-003 Wikipedia-Adjacent References | SEO/GEO Specialist | Marketing Lead · Exec Sponsor |
| S-004 Reddit & Community Presence | Marketing Lead | Technical Lead |
| S-005 Enterprise Positioning Content | Marketing Lead | Exec Sponsor · Content Lead |
| S-006 Localized Long-Form Content | Content Lead | SEO/GEO Specialist · Marketing Lead |
| S-007 Competitor Visibility Monitoring | SEO/GEO Specialist | Marketing Lead |
| S-008 Structured Data Standardization | Technical Lead | SEO/GEO Specialist |
| S-009 Google Business Profile Optimization | SEO/GEO Specialist | Marketing Lead |
| S-010 Developer Platform Architecture Guides | Technical Lead | Content Lead · SEO/GEO Specialist |
| S-011 X/Twitter Thought Leadership | Exec Sponsor | Marketing Lead · Content Lead |
| S-012 Mid-Market Specialization Messaging | Marketing Lead | Exec Sponsor · Content Lead |
What could go wrong,
and the mitigation.
| Scenario | Severity | Trigger · Impact · Mitigation |
|---|---|---|
| ChatGPT Sentiment Degradation | high | Trigger: ChatGPT sentiment drops below 70% from current 75%, or mention rate falls below 75%. Impact: composite score drops 5-8 points, moving from Good to Moderate tier. Mitigation: accelerate S-003 Wikipedia-adjacent seeding and prioritize authoritative third-party citations; deploy rapid response content addressing any negative sentiment sources. |
| Accenture Content Offensive | medium | Trigger: Accenture launches an AI optimized content campaign increasing mentions beyond 40, or gains first-position responses where Apex Teknologi appears. Impact: displacement from the enterprise consideration set as Accenture captures query intent permanently. Mitigation: accelerate S-005 enterprise positioning and S-012 mid-market differentiation. |
| Local Competitor Surge | medium | Trigger: Austin Vector IT or Lone Star Consulting Group achieve mention rates exceeding 60% or gain presence on models where currently absent. Impact: Austin market positioning erodes and local referral queries shift to competitors. Mitigation: escalate S-006 localized content and S-004 Reddit presence; deploy rapid local PR emphasizing Austin roots. |
| Model Algorithm Shift | low | Trigger: a major model update (particularly chatgpt or gemini) changes ranking factors, devaluing current content types or source preferences. Impact: baselines become unreliable and strategy requires mid-cycle reassessment. Mitigation: maintain diversified content strategy across all source types; avoid over-indexing on a single format or channel. |
| xai Positioning Decline | medium | Trigger: xai mention rate drops below 90% from 100%, or positive sentiment falls below 85% from 90%. Impact: loss of the only model with 100% mention rate undermines competitive positioning. Mitigation: accelerate S-011 X/Twitter thought leadership; increase posting frequency and engagement with Grok-indexed conversations. |
The stack, priced and prioritized.
| Vendor | Category | Cost | Priority | Why This Client |
|---|---|---|---|---|
| Profound (getprofound.ai) · alt Scrunch AI | Analytics | $500-1,500/mo | immediate | Purpose-built AI visibility monitoring across all 7 models; enables weekly tracking of mention rates and sentiment. |
| Clearscope · alt Surfer SEO | SEO | $170-350/mo | immediate | Content optimization for AI training corpus inclusion; supports S-001 and S-006 with semantic optimization. |
| Schema App · alt Yoast SEO Premium | Technical | $100-300/mo | immediate | Structured data implementation for S-002 and S-008, critical for consistent positioning depth across models. |
| Contently · alt Skyword | Content | $3,000-8,000/mo | phase 2 | Enterprise content platform for S-001 case study production and S-005 enterprise positioning content. |
| Muck Rack · alt Cision | PR | $500-1,000/mo | phase 2 | Media database for S-003 reference seeding and publication placement, addressing ChatGPT's 75% sentiment. |
| SparkToro · alt Audiense | Analytics | $150-300/mo | phase 2 | Audience intelligence for S-004 Reddit presence and S-011 X/Twitter program. |
| GitHub Enterprise · alt GitLab | Technical | $21/user/mo | phase 3 | Developer platform presence for S-010 technical architecture guides targeting deepseek indexing. |
The cost of waiting a quarter.
Apex Teknologi's 87 score reflects strong baseline visibility but masks critical vulnerabilities. Complete absence from digital transformation and cloud services queries means zero demand captured in the highest-value categories. ChatGPT's 75% sentiment, lowest among all models, will likely degrade further as competitors increase content velocity. Accenture's 33 mentions across all 7 models establishes dominant mindshare that compounds over time as models reinforce existing patterns. Local competitor traction from Austin Vector IT and Lone Star Consulting Group threatens the Austin positioning foundation. Without intervention, inconsistent positioning depth becomes permanent as models solidify current understanding: the 84% mention rate erodes to roughly 70% as competitor content displaces Apex Teknologi from training updates.
This roadmap was generated, not drafted.
Same engine, same discipline, run on your firm inside the Diagnose, Phase 1, or as a standing Sentinel GEO plan.