From 1a4fee43a20b6b0f3978063e6383eb028d19b904 Mon Sep 17 00:00:00 2001 From: David Gonoradsky Date: Tue, 19 May 2026 23:02:09 +0300 Subject: [PATCH 1/3] chore: add ai-bom agentic enrichment doc --- .../how-snyk-incorporates-generative-ai-into-the-platform.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/docs/snyk-data-and-governance/how-snyk-incorporates-generative-ai-into-the-platform.md b/docs/snyk-data-and-governance/how-snyk-incorporates-generative-ai-into-the-platform.md index 0750f5d2790f..69c239116337 100644 --- a/docs/snyk-data-and-governance/how-snyk-incorporates-generative-ai-into-the-platform.md +++ b/docs/snyk-data-and-governance/how-snyk-incorporates-generative-ai-into-the-platform.md @@ -55,6 +55,10 @@ Snyk uses multiple AI deployment strategies to balance performance, security, an
AttributeDetails
PurposeAllows the EVO AI-BOM to detect customer-specific AI assets, such as fine-tuned models.
AI models / deploymentAnthropic’s Claude models through GCP Vertex or AWS Bedrock.
Data processedCode snippets used to label whether patterns are AI assets.
Data retentionCustomer proprietary software code is not retained by the provider of these AI models.
Additional informationMore information about Evo AI-BOM Pattern Detection is available via the Customer portal.
+#### Evo AI-BOM Agentic Enrichment + +
AttributeDetails
PurposeAI-powered agent discovers AI components and relations that static analysis misses. The agent explores repository source code to identify AI-related components and relations (models, agents, tools, packages) and enriches the inventory with net-new findings.
AI models / deploymentAnthropic’s Claude models through GCP Vertex or AWS Bedrock.
Data processed
  • Repository source code
  • Existing inventory of AI components and relations from static analysis
Data retentionCustomer proprietary software code is not retained by the provider of these AI models.
Additional informationMore information about Evo AI-BOM Agentic Enrichment is available via the Customer portal.
+ ## Additional AI safeguards and controls Snyk has taken a proactive approach to AI governance by implementing robust policies, procedures and technical controls to encompass AI-specific considerations. In addition to Snyk's internal policies and controls, we maintain an overarching AI Governance Program managed by our cross-functional AI Advisory Board. From 8df46dd55a9cf724f62b847f690401e13f2b97bf Mon Sep 17 00:00:00 2001 From: David Gonoradsky Date: Fri, 12 Jun 2026 16:11:02 +0100 Subject: [PATCH 2/3] chore: update Agentic Enrichment table --- .../how-snyk-incorporates-generative-ai-into-the-platform.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/snyk-data-and-governance/how-snyk-incorporates-generative-ai-into-the-platform.md b/docs/snyk-data-and-governance/how-snyk-incorporates-generative-ai-into-the-platform.md index 69c239116337..0d93aaf77e95 100644 --- a/docs/snyk-data-and-governance/how-snyk-incorporates-generative-ai-into-the-platform.md +++ b/docs/snyk-data-and-governance/how-snyk-incorporates-generative-ai-into-the-platform.md @@ -57,7 +57,7 @@ Snyk uses multiple AI deployment strategies to balance performance, security, an #### Evo AI-BOM Agentic Enrichment -
AttributeDetails
PurposeAI-powered agent discovers AI components and relations that static analysis misses. The agent explores repository source code to identify AI-related components and relations (models, agents, tools, packages) and enriches the inventory with net-new findings.
AI models / deploymentAnthropic’s Claude models through GCP Vertex or AWS Bedrock.
Data processed
  • Repository source code
  • Existing inventory of AI components and relations from static analysis
Data retentionCustomer proprietary software code is not retained by the provider of these AI models.
Additional informationMore information about Evo AI-BOM Agentic Enrichment is available via the Customer portal.
+
AttributeDetails
PurposeAI-powered agent that operates in two parts: (1) Agentic Discovery - discovers first-party AI components (agents, tools, MCP servers/clients/resources, models) and the relations between them that static analysis misses; (2) Agentic Metadata Gathering - extracts tool descriptions and agent system prompts from already-discovered components by reading their source code.
AI models / deploymentAnthropic’s Claude models through GCP Vertex or AWS Bedrock.
Data processed
  • Repository source code
  • Existing inventory of AI components and relations from static analysis
  • Source code locations of already-discovered tools and agents for metadata extraction
Data retentionCustomer proprietary software code is not retained by the provider of these AI models. Tool descriptions and agent system prompts are stored in Snyk’s database as properties of their respective components.
Additional informationMore information about Evo AI-BOM Agentic Enrichment is available via the Customer portal.
## Additional AI safeguards and controls From 43256e5fa889107b24f1ef1ec7ddaac7a5bfa38b Mon Sep 17 00:00:00 2001 From: David Gonoradsky Date: Wed, 22 Jul 2026 11:19:49 +0300 Subject: [PATCH 3/3] docs: move the documentation to the correct file --- .../how-snyk-incorporates-generative-ai-into-the-platform.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/snyk-data-and-governance/how-snyk-incorporates-generative-ai-into-the-platform.md b/snyk-data-and-governance/how-snyk-incorporates-generative-ai-into-the-platform.md index 972b535a471a..3eaf6585a96f 100644 --- a/snyk-data-and-governance/how-snyk-incorporates-generative-ai-into-the-platform.md +++ b/snyk-data-and-governance/how-snyk-incorporates-generative-ai-into-the-platform.md @@ -55,6 +55,10 @@ Snyk uses LLMs from established AI providers, including OpenAI and Anthropic, th
AttributeDetails
PurposeAllows the EVO AI-BOM to detect customer-specific AI assets, such as fine-tuned models.
AI models / deploymentAnthropic’s Claude models through GCP Vertex or AWS Bedrock.
Data processedCode snippets used to label whether patterns are AI assets.
Data retentionCustomer proprietary software code is not retained by the provider of these AI models.
Additional informationMore information about Evo AI-BOM Pattern Detection is available via the Customer portal.
+#### Evo AI-BOM Agentic Enrichment + +
AttributeDetails
PurposeAI-powered agent that operates in two parts: (1) Agentic Discovery - discovers first-party AI components (agents, tools, MCP servers/clients/resources, models) and the relations between them that static analysis misses; (2) Agentic Metadata Gathering - extracts tool descriptions and agent system prompts from already-discovered components by reading their source code.
AI models / deploymentAnthropic’s Claude models through GCP Vertex or AWS Bedrock.
Data processed
  • Repository source code
  • Existing inventory of AI components and relations from static analysis
  • Source code locations of already-discovered tools and agents for metadata extraction
Data retentionCustomer proprietary software code is not retained by the provider of these AI models. Tool descriptions and agent system prompts are stored in Snyk’s database as properties of their respective components.
Additional informationMore information about Evo AI-BOM Agentic Enrichment is available via the Customer portal.
+ ## Additional AI safeguards and controls Snyk has taken a proactive approach to AI governance by implementing robust policies, procedures, and technical controls to encompass AI-specific considerations. In addition to Snyk's internal policies and controls, we maintain an overarching AI Governance Program managed by our cross-functional AI Advisory Board.