Captiva was built for a new era of search—where users ask questions to AI assistants like ChatGPT, Gemini, and Perplexity instead of typing keywords into Google. Traditional SEO still matters, but it’s only part of the picture. Most agencies focus on backlinks, meta tags, and keyword rankings. That’s great for Google, but LLMs don’t work the same way.
Captiva optimizes your brand for how AI models retrieve and recommend content. That means improving how your information is structured, ensuring your content is trustworthy and machine-readable, and aligning your brand narrative across the platforms that AI tools train on. Our software audits how your business shows up (or doesn’t) in real AI conversations and give you specific recommendations to increase your visibility. We want to help you rank #1 to AI engines—and make sure you’re referenced when it matters.
Yes. Captiva works in tandem with your existing SEO strategy by enhancing the things that matter to both traditional search engines and LLMs—such as structured data, content clarity, page hierarchy, and topical authority.
When we optimize your content for AI discoverability, we often surface and fix issues that also hold back your organic performance on Google. For example, poor schema markup or ambiguous entity labeling can confuse both AI models and search engines. Captiva helps align your content with a semantic structure that makes sense to machines, which often leads to improved performance across all channels—not just LLMs.We’re not replacing SEO—we’re expanding it. Think of Captiva as optimizing for the future of search.
It depends on the scope of your site, the changes you implement, and how quickly AI models refresh their training or retrieval indexes—but many of our clients begin to see significantly increased visibility within 1–2 months of working with Captiva.
Unlike traditional SEO, which often takes 6+ months to move the needle, LLMs update faster and respond immediately to structured, clear, and consistent information. In some cases, we’ve seen brands go from zero visibility to appearing in live AI responses in under 7 days. That said, we treat this like any strategy: long-term compounding value. Captiva doesn’t just give you analytics—we monitor your progress, benchmark you against competitors, and help you stay discoverable as models and algorithms evolve.We also provide live prompt tests, visibility trend reports, and alerts when your brand is mentioned (or omitted) by name in AI outputs—so you always know how you're doing.
Captiva is built for brands that rely on digital presence to drive growth. Whether you're a local service provider looking to dominate a local market, a DTC brand trying to compete with global names, or a B2B company building authority in a niche market—we help you show up in conversations.
We work especially well with owners and marketing teams who already invest in content, but want to take that investment further. If your blog, product pages, or service offerings aren't being referenced by AI models, you're leaving discoverability on the table.We also partner with agencies and consultants looking to add AI optimization into their stack. Captiva’s audit, optimization, and monitoring tools make it easy to add LLM-focused visibility into existing workflows.Bottom line: if people are searching for what you do—and asking AI for help finding it—Captiva helps you make sure they find you.
When you sign up for Captiva, you’re getting a tool built to help your portfolio stand out in AI search. The platform shows you how ChatGPT, Gemini, Perplexity, and other leading AI engines actually see and describe brands — what prompts they appear in, which sources are driving that visibility, and where they're missing out.
From there, Captiva turns those insights into clear, data-backed actions. You’ll see which pages need optimization, what structured data or schema to improve, and what content opportunities can help your brand appear more often and more accurately in AI-generated answers.
If you’re on a Pro or Enterprise plan, you also get daily visibility reports, competitive benchmarking, and the ability to track prompts, sources, and rankings across multiple brands or products. Captiva helps you understand your presence across AI search — and gives you the tools to improve it, automatically.
Captiva evaluates accuracy by running structured prompts across leading AI models and comparing the responses to verified information about your organization. We analyze every mention, claim, source, and citation to identify where models are correct, where they’re outdated, and where they’re missing key details entirely.
Our system scores accuracy across multiple dimensions — factual correctness, narrative consistency, source quality, and alignment with your brand’s approved messaging. From there, Captiva highlights the specific gaps affecting perception, including misinformation, incomplete descriptions, or reliance on low-quality third-party sources.
You get a clear, actionable report showing what AI is getting right, where it’s drifting, and the steps required to improve how models understand and represent you.
Captiva’s onboarding is designed to be fast, structured, and low lift for your team. Once your account is activated, we audit your existing content, technical setup, and AI visibility across models like ChatGPT, Gemini, Perplexity, Claude, and Grok. From there, we configure your workspace, set up custom prompt libraries, import key brand sources, and begin baseline accuracy and visibility testing.
Most organizations are fully deployed in a matter of days. You’ll receive a detailed kickoff report outlining your current AI presence, critical gaps, and the initial action plan for strengthening authority, consistency, and discoverability. Our team handles setup end-to-end so you can start receiving insights and recommendations immediately.
After deployment, Captiva continuously monitors how AI systems interpret and present your brand. We run recurring prompt tests, track source shifts, evaluate model changes, and identify new opportunities to improve visibility.
Your subscription includes ongoing optimization recommendations, content gap analysis, technical actions (schema, entity improvements, structured data updates), and narrative refinement. For managed service clients, our team executes the work for you, including content rewrites, knowledge updates, and AI-era information architecture improvements.
Captiva integrates smoothly with your existing workflows. We give your team a clear roadmap showing which updates matter most, why they matter, and the level of expected impact. Teams can assign tasks directly from Captiva’s Action Center, connect them to internal project tools, or export them into content calendars.
Whether you’re a team of one or a large enterprise marketing department, Captiva ensures that every action — from updating product pages to improving entity clarity — ties directly to improving your AI visibility and accuracy. The result is cleaner coordination, fewer random acts of content, and a unified strategy built for AI search.
Captiva measures performance continuously. Each recommended action is tied to specific visibility, authority, or accuracy indicators — and the platform tracks how those indicators shift as changes are published.
We test prompts weekly, monitor new citations or mentions, evaluate the quality of model responses, and benchmark your performance against competitors or category leaders. As models update, our systems update with them, ensuring your optimizations remain effective rather than becoming outdated.
Most importantly, Captiva closes the loop: you see exactly which actions moved the needle, which need refinement, and where new opportunities are emerging so your presence in AI search keeps strengthening month after month.
Every plan includes access to our support team and ongoing guidance, but higher-tier plans receive dedicated account management. That includes monthly strategy sessions, progress reviews, and proactive recommendations based on trends we’re seeing across the models.
Your account manager also helps prioritize tasks, review performance metrics, and make sure your content and technical teams have everything they need to execute. We operate as an extension of your team, ensuring you never fall behind on the changes happening across AI search.5
Captiva is built to layer into your existing environment without requiring major operational changes. During setup, we map your current tools — CMS platforms, analytics systems, content workflows, schema plugins, and data sources — to understand how your team publishes, updates, and measures content today.
The platform can push recommendations directly into your workflows through exports, integrations, or task syncing, so writers, developers, and strategists don’t need to adopt an entirely new process. Captiva simply adds intelligence on top of what you already do.
For organizations with more advanced needs, Captiva supports custom data ingestion, automated prompt testing, structured content pipelines, and ongoing monitoring that plugs into tools like Notion, Asana, Monday, Data Studio, and internal dashboards. The goal is to make AI-search optimization feel like an upgrade to your existing stack, not a disruption to it.
AI search optimization focuses on improving how large language models — like ChatGPT, Gemini, Claude, Grok, and Perplexity — understand, represent, and recommend your organization. These systems no longer send users to a list of links. They give direct answers, summaries, and recommendations pulled from the information they’ve learned.
Because buyers are increasingly asking AI models for product advice, service recommendations, and brand comparisons, organizations must ensure these systems interpret them correctly and cite reliable sources. AI search optimization helps brands stay visible, accurate, and competitive in this new answer-driven discovery environment.
AI models learn from a mix of public websites, structured data, third-party sources, and historical training snapshots. If your information isn’t clear, current, or represented across strong authoritative sources, models may fill gaps with assumptions, outdated data, or low-quality references.
Additionally, ongoing model updates can change how information is interpreted. Without consistent monitoring, organizations are often unaware that AI systems are describing them inaccurately. AI search optimization addresses this by identifying inaccuracies, tracing them to their source, and guiding the fixes that improve model understanding.
AI models use a broader set of signals than traditional search engines. They rely on entity clarity, structured data, semantic relationships, historical descriptions, trustworthy citations, and the consistency of information across the open web.
If your brand lacks structured context, clear positioning, authoritative mentions, or consistent language across your digital footprint, models may struggle to represent you accurately. AI search optimization helps organizations strengthen these signals so models can confidently retrieve and describe them in answers.
The AI search ecosystem is moving dramatically faster than traditional SEO. Major models update weekly or monthly, compared to Google’s slower and more predictable timeline. These updates often shift how brands are interpreted, which sources are trusted, and what answers models produce.
Because of this rapid evolution, organizations need real-time visibility into how AI systems describe them — and a clear strategy for keeping information correct, current, and competitive. AI search optimization provides that layer of intelligence and ensures brands stay discoverable in an environment that changes constantly.
AI models don’t rely on a single source or ranking system. They synthesize information from thousands of signals — websites, structured data, third-party databases, news coverage, historical snapshots, and even outdated versions of your own content. Because the model combines all of this into a single answer, any inconsistency or misinformation anywhere in your footprint can influence the output.
That means organizations can’t “optimize one page and be done.” They need a coordinated approach: consistent entity definitions, clean structured data, authoritative citations, aligned messaging, and a strong presence across trusted sources. AI search optimization brings this all together so models have accurate, stable context to draw from.
Different queries have different levels of structured data, authoritative sources, competitive content, and clarity in how brands describe themselves. For example, healthcare, finance, and higher education have rich external data sources that models lean on, while emerging SaaS categories may have little structured information.
This means some industries are automatically favored in AI search, while others are harder for models to interpret. AI search optimization helps level the playing field by filling in missing signals, improving clarity, and building the authority needed for models to trust and surface an organization more often.
