Technical accessibility
Crawlability, indexability, rendering, canonicalization, internal linking, crawler controls, WAF/CDN and structured data where appropriate.
AI Search Optimization Services for B2B Companies
AI visibility is not a one-time optimization project.
Lexogrine helps B2B companies continuously measure how they appear across AI-driven discovery, identify the highest-impact opportunities, implement technical improvements and validate what actually changed.
Request an AI Search Audit- 1.Establish a reliable baseline
Buyer prompts, competitors and technical context.
- 2.Ship the agreed improvements
Technical capacity and coordinated execution.
- 3.Validate and keep improving
Evidence to guide the next monthly cycle.
Typical initial engagement: 3 months
Monthly continuation afterward.
AI visibility keeps changing
Models evolve. Retrieval systems change. New sources become influential. Competitors publish new information. Your website changes. Buyers use different language to describe the same problems.
A single audit can establish where you stand. It cannot permanently optimize a moving system.
AI Search Optimization is the ongoing process that follows the baseline.
Audit establishes the baseline. Optimization is what happens next.
AI Search Optimization is a continuous operating system
- 1.
Measure
Track the discovery environment.Track controlled buyer prompts across the relevant AI surfaces, competitors, markets and languages.
Controlled baseline - 2.
Understand
Find the gaps and their context.Identify where competitors replace you, which sources influence answers, how your company is portrayed and where gaps exist.
Opportunity map - 3.
Prioritize
Separate opportunity from noise.Separate high-impact opportunities from noise and established technical work from experimental hypotheses.
Priority backlog - 4.
Ship
Implement and coordinate.Implement technical improvements and coordinate wider changes with marketing and content teams.
Agreed implementation - 5.
Validate
Measure the same environment.Measure the same discovery environment again.
Measured outcome - 6.
Repeat
Define the next iteration.Use the resulting evidence to define the next iteration.
Next cycle
Every result informs the next cycle.
Optimize the systems that shape AI discovery
Not every AI Search problem is a content problem.
Information architecture
Site hierarchy, product and service architecture, entity consistency, CMS models, templates and structured relationships.
Source environment
Influential sources, competitor citations, missing evidence and inaccurate or outdated third-party information. PR and outreach ownership is agreed with your team.
Buyer information coverage
Missing use cases, weak comparison information, unanswered buyer questions, unclear differentiation and missing evidence.
When optimization requires software changes, we can ship them
The recommendation often requires someone to change the software.
AI Engineering
Agents, AI-enabled products, model integrations and supporting infrastructure.
Software Engineering
Customer platforms, internal systems, APIs and data-intensive applications.
Cloud & Infrastructure
Architecture, migrations, DevOps, integrations and production operations.
Mobile
Native and cross-platform products for customers, teams and connected services.
Every optimization cycle starts and ends with measurement
AI Visibility Monitoring is included in an AI Search Optimization engagement.
Presence
Are you surfaced?
Prominence
How visible are you?
Portrayal
How are you described?
Persuasion
Are you merely mentioned or recommended?
ChatGPT Search
Google AI Overviews- Google AI Mode
Gemini
Microsoft Copilot
Perplexity
Internal tooling is a Lexogrine capability used to inform the work and validate the outcome.
Turn recommendations into testable hypotheses
- 1.Observation
A competitor repeatedly appears for an important comparison-intent prompt.
- 2.Hypothesis
The competitor exposes clearer, technically accessible comparison information.
- 3.Change
Create or restructure the required information.
- 4.Measurement
Run the defined prompt cohort again.
- 5.Result
Determine whether the observed pattern changed enough to justify the next action.
Illustrative methodology. The example describes a hypothesis to test, not a claimed result or a guaranteed cause.
Built around your existing marketing organization
Lexogrine owns
- AI Search measurement
- Competitor/source analysis
- Technical diagnosis
- Strategic prioritization
- Engineering
- Experimentation
- Validation
We collaborate on
- Information architecture
- Content requirements
- Buyer journey priorities
- Implementation sequencing
Your team can continue owning
- Editorial production
- Thought leadership
- Digital PR
- Outreach
- Community
- Broader demand generation
AI Search Optimization builds on strong SEO fundamentals
Traditional Search measurement
Rankings / Impressions / Clicks / Traffic
AI discovery adds
Presence / Competitors / Sources / Portrayal / Recommendations
We extend proven SEO and engineering fundamentals with measurement designed for AI-driven discovery.
We do not replace them with speculative GEO tactics.
What an AI Search Optimization engagement looks like
Typical initial engagement: 3 months
The initial period creates enough operating space to establish the baseline, implement meaningful changes and complete the first validation cycle. After that, the program can continue monthly.
An operating timeframe, not a guaranteed results timeline.
- 1.Establish the baseline
Define prompts, surfaces, competitors, markets and current technical environment.
- 2.Build the priority backlog
Convert findings into technical, strategic and experimental priorities.
- 3.Run the first implementation cycle
Ship agreed technical work and coordinate changes owned by other teams.
- 4.Validate and iterate
Refresh measurement and decide what comes next.
We apply the same process to a product we operate ourselves
LHM is Lexogrine's own software platform for professional esports broadcast production. It competes in highly specialized B2B categories including CS2 HUDs, Valorant HUDs, League of Legends HUDs, observing overlays and HUD management software.
We have built a strong organic discovery footprint around those categories and repeatedly observe LHM being surfaced by leading AI systems when buyers research relevant solutions.
67%
Recommendation inclusion across the defined LHM buyer prompt cohort
5/7
Monitored AI discovery surfaces where LHM appears
72%
Response share of voice against the defined competitor set
LHM gives us an environment where we control the product, website, technical architecture, content structure and implementation roadmap, while observing how those systems translate into traditional search and AI-driven discovery.
It allows us to apply and validate the same measurement principles we use in client engagements against a product we own and operate commercially.
These reviews describe technical quality, problem solving, responsiveness, delivery and collaboration. They are engineering references, not AI Search case studies.
What clients say after we ship
These reviews describe our software engineering, design and development work. They demonstrate delivery experience, not measured AI Search visibility results.
It was obvious that Lexogrine wanted to create the best possible solution customized for us.
Read on ClutchLexogrine was even able to add features and improve the platform’s speed in a mere week!
Read on ClutchThey’ve stepped out of their way to deliver things out of their interest for the project.
Read on ClutchTheir turnaround times were fantastic.
Read on ClutchOne of the best agency experiences we have had bar none.
Read on ClutchLexogrine is an incredibly hardworking and dedicated group of individuals that I rarely see at development companies.
Read on ClutchTheir project management skills and problem-solving approach were impressive.
Read on ClutchThey knew exactly what we wanted and filled our needs perfectly.
Read on ClutchLexogrine is good. The team knows what they’re doing and they have a strong aesthetic.
Read on ClutchThey listen well and provide feedback to really fulfill the client's overall vision.
Read on Clutch
Selected review excerpts from software, design and development projects.
Built for B2B companies ready to act on the findings
- B2B buying journey
- Meaningful deal value
- Research-heavy discovery
- Established digital presence
- Existing marketing/content capability
- Ability to implement technical changes
- Willingness to operate continuously
Build an AI Search improvement loop your team can actually operate
If a reliable baseline already exists, Lexogrine can evaluate a direct move into Optimization. For most companies, AI Search Audit is the preferred starting point.
Explore the complete AI Search approach