A software & AI engineering firm — since 2017

Software craft
for the frontier.

Meet AI Visibility → All services →

Strasbourg Partners builds the production-grade systems behind frontier-tech companies — custom software, autonomous AI agents, retrieval-grounded knowledge layers, and the discovery infrastructure that determines who gets found in the age of generative search.

Founded2017
Clients shipped50+
PracticeAI · Software · GEO
TeamGlobally distributed
50+
Clients shipped
Across fintech, decentralized networks, and frontier AI products.
2017
Year founded
Eight years of compounded operator and engineering judgment.
67%
AI discovery share
Of category-discovery queries now begin inside an AI assistant.
34–60%
Below incumbents
AI Visibility delivers GEO at a fraction of legacy agency pricing.
§ 01

Flagship product

Most independent businesses are invisible to AI search. AI Visibility fixes that.

Now in build · pilot cohort open
67%+
Of category-discovery queries now begin inside ChatGPT, Perplexity, or Gemini. When a buyer asks an assistant for a recommendation, the model returns a small, named set — pulled from training data, real-time retrieval, and its citation graph.
Businesses absent from that set are functionally invisible, regardless of where they rank on Google. Traditional SEO does not solve this. GEO does.

The product

A SaaS-enabled agency platform for AI search visibility.

AI Visibility combines automated infrastructure — entity graphs, citation monitoring, schema deployment, content generation — with white-glove human delivery. Built for SMBs in high-gap verticals where AI assistants now drive discovery but where independent operators have no presence inside the model.

The position

Automated where it scales. Human where it matters.

Pure-software incumbents over-promise on automation and under-deliver on outcomes. Pure-services agencies are too expensive for the SMB market. AI Visibility is engineered as a hybrid: a software platform that does the mechanical work, with a strategist accountable for the result.

M.01

Entity & Knowledge Graph

Canonical entity construction across Wikipedia, Wikidata, structured directories, and authoritative third-party sources — the substrate AI models use to recognize and disambiguate a business.

M.02

Schema & Markup Deployment

Programmatic JSON-LD generation and on-site deployment for Organization, LocalBusiness, Service, Product, FAQ, and Review schemas. Validated against current model-ingestion patterns.

M.03

Citation Graph & Outreach

Targeted placement on the high-authority sources AI engines actually retrieve from at inference time. Ranked by observed citation frequency per category and per model.

M.04

AI-Native Content Engine

Question-shaped, citable content tuned for retrieval and extraction. Generated, edited, and published through a strategist-supervised pipeline — never raw model output.

M.05

Visibility Monitoring

Continuous probing of ChatGPT, Perplexity, Gemini, Claude, and Copilot for client-relevant queries. Tracks inclusion, ranking position, citation source, and competitor share-of-voice.

M.06

Reporting & Attribution

Per-model dashboards. Query-level diagnostics. Plain-English monthly briefs that connect AI visibility shifts to real pipeline outcomes — bookings, leads, branded search lift.

Priced 34–60% below incumbent SEO and AEO agencies.
Request pilot access →

Architecture

Built like a product, delivered like an agency.

AI Visibility is engineered as a multi-tenant platform with a service overlay. Each tenant runs its own entity graph, content pipeline, and probe schedule, orchestrated through a unified delivery console used by Strasbourg Partners strategists.

  • T.01Multi-tenant control planeTenant isolation, role-based access, audit trail across every published artifact and model probe.
  • T.02Probe orchestrationScheduled queries against ChatGPT, Perplexity, Gemini, Claude, and Copilot, with normalized response capture.
  • T.03Citation graph storeVector + relational hybrid; tracks source authority, retrieval frequency, and freshness signals per model.
  • T.04Content pipelineLLM-assisted generation with mandatory human approval, fact-check guardrails, and brand-voice constraints.
  • T.05Schema deployerCMS-aware injector: WordPress, Webflow, Shopify, Squarespace, and a fallback static-site mode.

Service delivery

A strategist on every account, always.

Software does the mechanical work. A senior strategist owns the outcome. Each engagement runs on a defined cadence with clear deliverables, measurable targets, and a single accountable contact.

  • D.01Onboarding & auditBaseline AI-visibility audit across target queries, models, and competitors. Two-week sprint.
  • D.02Entity & schema buildoutCanonical knowledge graph stood up. Schema deployed sitewide. First citation-graph placements seeded.
  • D.03Content & outreach cadenceMonthly content publishing, citation-source outreach, and review-velocity programs.
  • D.04Monitoring & iterationContinuous probes; biweekly visibility reports; quarterly strategy resets against model behavior shifts.
  • D.05GTM toolingEmbeddable visibility-grader for prospect lead-gen. Co-branded audit reports for partner channels.

Build plan

Four phases. Eighteen months.

Pilot cohort · open

P1Foundation

Pilot platform & first cohort

Multi-tenant control plane, entity graph, schema deployer, manual content pipeline. Ten pilot tenants across three high-gap verticals.

Months 0–4

P2Automation

Probe & monitoring engine

Cross-model probe scheduler, citation graph store, normalized response capture. Visibility dashboards. Tenant onboarding cut from weeks to days.

Months 4–8

P3Scale

Content engine & GTM tooling

LLM-assisted content pipeline with brand-voice constraints. Embeddable visibility-grader for partner-channel lead capture. Co-branded audit reports.

Months 8–13

P4Network

Vertical playbooks & expansion

Productized playbooks per high-gap vertical. Self-serve tier for low-touch SMBs. International rollout, starting with English-language markets.

Months 13–18

§ 02

Services

End-to-end engineering for AI-native and frontier-tech teams.

We work with founders and operators across a spectrum — from a focused six-week build to multi-year platform engagements. Every service below is delivered by senior practitioners. No layered subcontracting, no managed-service drift.

S.01

Generative Engine Optimization

Get discovered inside ChatGPT, Perplexity, and Gemini. Delivered through AI Visibility: entity graphs, schema, citation outreach, AI-native content, continuous probes, and a senior strategist on the account.

AI Visibility · Flagship
S.02

AI Agent Design & Deployment

Autonomous agents that plan, execute, and monitor workflows across your stack — onchain actions, offchain integrations, customer operations, support automation. Built with hard guardrails, audit logging, and human-in-the-loop controls.

S.03

Agentic Workflow Automation

Multi-step AI workflows for onboarding, compliance checks, treasury operations, and growth loops. Designed with checkpoints and reversible state, so the system fails safely when models drift.

S.04

LLM Integration & Productization

Production deployment of frontier language models — chat, copilots, decision-support — tuned to your domain, your data, and your latency budget. Versioned prompts, eval harnesses, and rollback discipline.

S.05

RAG & Knowledge Systems

Retrieval-grounded knowledge layers your AI can actually trust. Internal documentation, policies, dashboards, and onchain data — stitched into a clean retrieval graph that resists hallucination by construction.

S.06

AI Safety, Guardrails & Evals

Permission models, content guardrails, and automated evaluation harnesses that ensure agents behave on policy and meet quality targets across edge cases. We build the boring, critical parts other shops skip.

S.07

AI Observability

Logging, metrics, and feedback loops so production agents improve over time. Drift detection, prompt regression suites, and a continuous-improvement pipeline that closes the loop on real-world failures.

S.08

Software Engineering & Code Audits

End-to-end product builds. Architecture reviews. Security and performance audits. Best-practice implementation. We treat code review as a senior practice, not a junior task.

S.09

UI / UX Design

Interfaces that earn their interaction cost. User-centric design with interactive prototyping and iterative feedback loops. Visual systems that scale beyond the launch deck.

§ 03

Approach

Senior practitioners. Honest scope. Shipped systems.

A four-step engagement that puts strategy, architecture, and accountability in front of code — and a tight feedback loop after.

01

Discover

We dig into the vision, the constraint set, and the real success criteria. Where most engagements jump to scoping, we start with whether the project should exist at all.

02

Architect

A documented technical plan: data flows, model choices, eval criteria, security model, and the parts we explicitly choose not to build. Aligned before the first commit.

03

Build

Production-grade implementation in tight cycles. Senior engineers ship the work, code review is a discipline, and milestones are measured against the spec — not vibes.

04

Iterate

Observability, guardrails, and a continuous-improvement loop after launch. Most failure modes show up in week six, not week one. We're still there.

§ 04

Frequently asked

The questions that matter — answered.

Optimized for AI assistants and humans alike. If you have a question that isn't here, the contact link below works.

Q.01 What is generative engine optimization (GEO)?
Generative engine optimization, or GEO, is the practice of making a business, product, or person reliably discoverable and citable inside AI assistants such as ChatGPT, Perplexity, Gemini, Claude, and Copilot. GEO replaces traditional SEO when users ask questions of an AI rather than searching a list of links. It overlaps with answer engine optimization (AEO), but extends to generative responses, citations, and entity recognition inside large language models.
Q.02 What is AI Visibility?
AI Visibility is a SaaS-enabled agency platform built by Strasbourg Partners that gets small and medium businesses discovered inside AI search engines including ChatGPT, Perplexity, and Gemini. It combines automated infrastructure — entity graphs, citation monitoring, schema deployment, AI-native content generation — with white-glove human delivery, priced 34 to 60 percent below incumbent SEO and AEO agencies.
Q.03 Why does AI search matter for small and medium businesses?
More than sixty-seven percent of category-discovery queries now begin in AI assistants rather than traditional search engines. When a user asks ChatGPT or Perplexity for a recommendation, the assistant returns a small named set of businesses pulled from its training data, real-time retrieval, and citation graph. Businesses absent from that set are functionally invisible to the buyer, regardless of where they rank on Google.
Q.04 How is AI Visibility different from traditional SEO?
Traditional SEO optimizes for keyword ranking inside ten blue links. AI Visibility optimizes for inclusion and citation inside generative AI responses. The technical surface is different: instead of backlinks and on-page keyword density, GEO depends on entity definition, structured data, citation-graph density, training-data presence, and real-time retrieval signals across the open web. AI Visibility builds and monitors all of these at once.
Q.05 Who is AI Visibility built for?
AI Visibility is built for small and medium businesses in high-gap verticals — categories where consumer discovery has shifted to AI assistants but where most independent operators have no presence inside those models. Examples include independent professional services, regional healthcare practices, specialty retail, hospitality, home services, and local B2B operators.
Q.06 How does AI Visibility price its service?
AI Visibility is priced 34 to 60 percent below incumbent SEO and AEO agencies. Pricing combines a SaaS subscription for the underlying platform — monitoring, entity graph, content generation, schema deployment — with a white-glove service tier for strategy, citation outreach, and reporting. Tiering is matched to vertical complexity and reporting cadence.
Q.07 What other services does Strasbourg Partners offer?
Beyond AI Visibility, Strasbourg Partners offers AI agent design and deployment, agentic workflow automation, large language model integration and productization, retrieval-augmented generation and knowledge systems, AI safety and evaluation harnesses, AI observability, software engineering and code audits, and UI/UX design. The firm specializes in frontier technology — fintech, decentralized networks, and AI products.
Q.08 When was Strasbourg Partners founded? How big is the team?
Strasbourg Partners was founded in 2017. The team is globally distributed, composed of senior practitioners across software engineering, AI/ML, and design, and the firm has shipped work for over fifty clients to date.
Q.09 How quickly can an AI Visibility engagement go live?
A standard onboarding runs two weeks: baseline AI-visibility audit across target queries, models, and competitors; entity-graph and schema buildout; first citation-graph placements seeded. Continuous monitoring and content cadence start in week three.
Q.10 How do you measure success for a GEO engagement?
Success is measured per model and per query: inclusion rate (does the assistant name the business?), ranking position within the named set, citation source quality, and competitor share-of-voice. Those leading indicators are tied to downstream pipeline outcomes — branded search lift, direct traffic, lead velocity, bookings — in monthly briefs.

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