How Latent Increased Organic Traffic 76× by Fixing How Search Engines and AI Systems Interpret Its Site

At a Glance

The Challenge: Strong Capability That Search Engines Ignored

Latent is a highly capable healthcare software development firm.
However, their organic presence did not reflect that capability.

Despite legitimate experience in healthcare software, Latent struggled to appear for high-value queries such as:

• “Custom healthcare software development”

• “Healthcare product engineering partners”

Instead, traffic was limited to low-value local searches, with 97% coming from India and no meaningful competitive discovery.

The issue was not the quality of work.
It was how machines interpreted the site.

The Constraint: Poor Machine Interpretation

From the perspective of search engines and AI systems, Latent’s site had three critical issues:

• Unclear specialization: Healthcare focus was not explicitly defined in a way LLM’s could extract.

• Weak trust signals: Broken and incomplete authority paths suppressed ranking potential.

• Low contextual coverage: Content was too narrow to establish industry-level relevance.

As a result, Latent did not appear as a healthcare software provider.
It appeared as an undefined services site with limited relevance.

The Solution: Fixing How Machines Read the Site

Latent used Erlin.ai to correct how search engines and AI systems parse, classify, and rank their site.

1. Making Services Explicit and Machine-Readable

Action: Clearly define organization type, services, and healthcare focus using structured formats.

Latent’s services were rewritten and structured so machines could unambiguously understand:

• What the company does

• Who it serves

• Which industry it belongs to

Impact:
Search engines began classifying Latent correctly within healthcare software categories.

2. Repairing Trust and Authority Signals

Action: Identify and fix broken authority paths.

Erlin identified broken backlinks and missing industry references that weakened Latent’s trust profile. These were repaired and reinforced through relevant healthcare software directories and references.

Impact:
Latent crossed the minimum trust threshold required to rank competitively.

3. Expanding Context Beyond Services

Action: Publish industry-level content tied to healthcare software trends.

Latent deployed content addressing broader industry topics (e.g., healthcare software trends and regulations), allowing machines to associate the domain with research-phase and evaluation-phase queries.

Iimpact:
The site became eligible to rank beyond branded and local searches.

Results: A Step Change in Visibility

1. 76× Increase in Organic Traffic

Once machine interpretation issues were resolved, traffic increased Significantly to 76 times than what it was erlier

This growth appeared as an abrupt change, not a gradual curve indicating the removal of suppression rather than incremental optimization.

2. AI Traffic Appeared for the First Time

Latent began receiving traffic directly from AI systems:

• 157 qualified AI sessions

• 0 → 2.4% AI share of traffic
  
  

This confirmed that AI systems were now able to retrieve and recommend Latent for relevant technical questions.

Conclusion

Latent demonstrated that many visibility problems are not marketing problems,they are interpretation problems.

By fixing how search engines and AI systems classify, trust, and retrieve their site using Erlin.ai, Latent unlocked a scalable organic channel and achieved 76× growth in a single quarter.

When machines can understand what you do, growth follows.