Precise AI answers for an investigations firm, case by case

Who the client is

Specialist investigations. Berea Intelligence helps buyers investigate the people, companies and assets behind high-stakes decisions. Its work includes corporate due diligence, asset tracing, financial investigations and cross-border matters that require coordination with legal, tax and banking specialists.

Ongoing engagement. We began working together in July 2026. This case covers approximately the first three months, through October 9. The ongoing engagement is EUR10,000 per month.

What they came to us with

Buyer confidence. Berea was launching a niche business built around personal conversations. Prospects researching the firm needed AI to explain who they were speaking to, what the team could do and whether its experience matched their problem.

I've spoken to Berea Intelligence. Who are they, and can they help with my situation?

A useful answer has to explain

• What Berea does and whom it serves
• Which of its past cases match the problem
• What the buyer still needs to check

Specific questions. The critical moment came after an introduction, when a prospect asked AI who Berea are and whether they can help. Berea wanted those answers to draw on its expertise, methods and cases in enough detail to support a serious conversation.

What they got

Detailed brand answers. By the third month, the captured AI answers described Berea’s services and connected a specific buyer question to a relevant published case. The client reported a change from AI having no information about the brand to explaining the expertise documented on its website.

• 1
  Brand understanding

  The captured brand answer describes Berea's core investigative services and intended clients

• 2
  Relevant experience

  A supplied answer cites a relevant published case and explains why it matters

• 3
  Buyer-fit guidance

  The answer separates relevant experience from the jurisdiction-specific expertise the buyer should check

• 4
  Commercial progress

  Around ten serious calls that we considered pre-qualified, by our informal assessment

Repeatable publishing. Berea also gained a working content production system for turning its expertise into service explanations and case studies, supported by ongoing strategic guidance.

The situation before the engagement

Business context

Small buyer pool. Berea serves people facing specific, consequential problems. Each conversation needs to establish trust, relevant experience and a workable scope. A prospect may already have an introduction but still need to investigate the firm before sharing sensitive details.

Website and content

Experience to explain. The launch required the team’s experience to become accessible public material. Prospects needed to understand the problem in each case, Berea’s role and the work delivered, while confidential client information remained protected.

Traffic sources

Personal conversations. Direct introductions and discussions were central to the launch. Branded AI research was intended to support that buying process: after hearing about Berea, a prospect could ask an assistant about the firm and assess whether to continue the conversation.

Search presence

Little brand knowledge. Berea’s founding partner reported that AI initially knew nothing about the firm. That left prospects with little help assessing its suitability when they searched the name.

Previous approach

Publishing difficulty. The team had expertise to share but struggled to produce detailed case studies and positioning material consistently. The engagement brought research, priorities and a production system to that work.

The strategy we planned and why

Commercial and search priorities

Earn informed consideration. We focused on what buyers needed to learn after hearing Berea’s name. The strategy connected the firm’s positioning to the questions prospects asked, with published experience supporting each service claim.

• Company understanding. Explain what Berea does and which buyers it serves.
• Relevant experience. Show how previous work relates to a prospect’s specific problem.
• Scope clarity. Explain Berea’s role and where local specialists participate.
• Qualified conversations. Help prospects arrive with a better understanding of fit and the questions still to resolve.

Technical SEO priorities

Audit foundation. We delivered a technical SEO audit alongside the positioning work. The content strategy depended on a public website that could serve as a source for search and AI answers.

Content strategy and production order

Expertise into content. Service explanations established what Berea could help with. Case studies supplied concrete accounts of its experience. The content production system made it practical to keep developing both as the team documented more of its work.

Why the strategy fit

Relevant proof. A buyer considering a sensitive investigation needs to know why this firm suits the problem. Detailed case material gives that buyer something specific to examine and gives AI a source for explaining the firm’s experience.

"Their strategic thinking and systematic high-tech approach are impressive."

What we did

Agency and client responsibilities

Joint delivery. We led the search strategy and developed the prompts and content production system. Berea contributed its expertise and case material. Together, we used the system to produce service pages and case studies.

1. 1
   Research, strategy and technical SEO audit
   • Buyer questions
   • Competitor AI coverage
   • Technical SEO audit
   • 90-day strategy
2. 2
   AI content production system
   • Prompts
   • Reusable instructions
   • Code
   • Content structure
3. 3
   Ongoing production and answer reviews
   • Case writing
   • Service content
   • AI answer reviews

Weekly coaching calls with the Berea team, from July 2026 and continuing

Phase 1: Research, strategy and technical audit

Research and priorities. We examined buyer questions and competitor AI coverage, then connected the findings to Berea’s positioning. The technical audit and a 90-day strategy gave the team an execution plan with reasons for each priority.

Phase 2: Building the AI content production system

Working production system. We supplied prompts, reusable instructions, code and a structure for producing content. The system supported writing about Berea’s services and case experience in detail, giving the team a repeatable way to explain its work.

Practical coaching. We met weekly to review progress, resolve obstacles and guide execution. Anna described that support in her GoodFirms review.

"They guided our team through execution with regular coaching calls and strategic direction."

Phase 3: Ongoing production, measurement and improvements

Continuing work. The engagement continues with case writing, service content and qualitative review of selected AI answers. The questions focus on whether a prospect receives a useful explanation of Berea’s capabilities, experience and suitability.

Results

Search and AI results

Brand recognition. In the first example below, a buyer whose business lost crypto assets to fraud asks whether Berea, which they were recommended, has relevant expertise. The answer matches Berea’s services to the situation, from blockchain tracing to evidence for asset freezing, and points to the company’s website.

A buyer whose crypto assets were stolen asks whether Berea has relevant expertise

We judge the accuracy of the description of who Berea is

• Names Berea's investigative services correctly
• Matches those services to the buyer's situation
• Points to Berea's own website

Specific buyer fit. In the follow-up, the buyer asks whether Berea has traced assets to a person. The answer cites two published Berea cases: an interim crypto seizure in a Portuguese divorce and cross-border asset tracing against a Swiss banking group.

Measurement approach. These two examples illustrate answer quality: the services match Berea’s offer, and the case details match its published cases. The client’s review supplies the before-and-after account and describes its broader assessment of citations, sentiment, recommendations and accuracy as observational.

The follow-up asks for a case where Berea traced assets to a person

We judge the precision of the case details and whether it picks the closest case

• Case details match the published cases
• Recommends the closest cases Berea has published
• Links to the cases on Berea's website

Business results

Early commercial conversations. During the first three months, we informally assessed around ten serious calls as pre-qualified. These conversations formed the early commercial context for the positioning work.

Intended buying sequence. A prospect hears about the firm, researches it through AI and encounters relevant expertise before continuing with more specific questions. This is the role branded AI research was designed to play in Berea’s relationship-led sales process.

Conclusion

Expertise made accessible. Berea launched with experience that needed to be explained. By the third month, the captured AI answers could describe its services and bring a relevant case into a buyer’s evaluation.

Continued support. The ongoing work gives Berea a way to keep documenting its experience and assess how AI presents it. Prospects can examine a more detailed account of the firm before deciding to share their own problem.