Symosis engineers AI-assisted investigation, analysis, and automation within your existing security environment.
We connect data, tools, and workflows to help practitioners gather evidence, review findings, and coordinate action—with defined permissions, human oversight, and measurable acceptance criteria.
Security teams spend valuable time collecting context, moving information between tools, preparing access reviews, and assembling evidence.
Symosis identifies where AI-assisted analysis can help, where conventional automation is sufficient, and which decisions require practitioner review.
Each engagement starts with a workflow, a baseline, and an evaluation plan.
Retrieve relevant asset, identity, vulnerability, and event context. Assemble timelines and draft investigation summaries linked to supporting evidence.
Outputs
Investigation workflows, evidence-linked summaries, evaluation results, and analyst runbooks.
Connect and normalize approved data sources. Establish identity and asset mappings, access controls, quality checks, and governed retrieval.
Outputs
Connectors, data pipelines, schemas, quality monitoring, and operating documentation.
Combine configuration, entitlement, ownership, and available usage evidence to support risk reviews and remediation decisions.
Outputs
Contextualized findings, access-review packages, approval workflows, and reporting integrations.
Enrich findings with asset and business context. Apply agreed prioritization rules, prepare remediation summaries, and coordinate approved ticket updates.
Outputs
Prioritization workflows, ticketing integrations, action tracking, and validation reporting.
Collect evidence from approved sources and assist with organization, control mapping, narrative preparation, and reporting.
Outputs
Evidence pipelines, source-linked drafts, review workflows, and provenance records.
Each capability defines:
Initial deployments can operate in read-only or recommendation mode. Additional authority is introduced through agreed evaluation and approval.
Depending on the use case, evaluation may consider:
Results determine the next step: refinement, limited deployment, or production rollout.
Select a repeatable problem with clear ownership.
Assess data quality, permissions, integrations, and constraints.
Build the workflow with oversight and failure handling.
Evaluate representative cases and edge conditions.
Deploy with training, monitoring, and a maintenance process.
Choose one workflow with usable data and a measurable need: alert enrichment, investigation summarization, SaaS finding analysis, access-review preparation, or evidence collection.
For standard API synchronization and rule-based workflows, explore Security Automation & Custom Integrations.
Client evidence · pending approval
A sanitized technical example, sample deliverable or approved case study for this service will appear here once approved. No results are shown until then.
Our approach uses AI to remove repetitive work; analysts retain decision authority on consequential actions.
Usually alert enrichment, investigation summarization and evidence collection, because they are repetitive and easy to verify.
Through scoped identities, least-privilege access and logging of every AI action.
Tell us where your team spends time gathering information, reviewing findings, or coordinating action.