Agents
Agents and services that take real action on real systems.
Security-led engineering
Secure the execution layer
Mochavi is an engineering practice for sensitive production systems. We review and build the layer where software actually acts — agents, tools, data access, and the controls around them.
The execution layer
Where software acts
The layer where intent becomes action — and where production risk concentrates.
Whether it is an AI agent or a conventional service, the same boundary decides what it can reach: tool integrations, permissions, data access, approvals, and guardrails. That boundary is where we focus.
Tools
Integrations and tools that grant capability and reach.
Data
Data access scoped to exactly what the work requires.
Controls
Approvals, audit, and guardrails you can actually rely on.
What we do
Security-led engineering, end to end.
One practice across review and build. We assess the execution layer of systems already in production, and we build new ones with those controls from the start.
Agentic Security Review
Our flagship engagement. A focused review of AI agents, MCP integrations, tool permissions, data access, approvals, and guardrails before they reach production.
- Agent behavior and execution paths
- Tool and MCP permission mapping
- Data access and leakage exposure
- Approvals, audit logs, and guardrails
Sensitive System Review
Security and design review for production systems that touch customer data, credentials, payments, or business-critical workflows.
- Trust boundaries and data flow
- Authentication and authorization paths
- Secrets, access scope, and blast radius
- Logging, audit, and incident readiness
Secure Engineering & Tooling
Designing and building developer tooling, internal systems, and automations where data handling and correctness are non-negotiable.
- Local-first and privacy-respecting design
- Internal tools and workflow automation
- Hardening of existing systems
- Pragmatic, reviewable implementations
AI & Automation Implementation
Putting AI features and automation into real systems with the execution-layer controls they need to be trusted in production.
- Agent and workflow integration
- Scoped tool and data permissions
- Human approval and oversight paths
- Observability from day one
Risk surface visibility
The risk surfacebecomes legible
We map how a system behaves, what it can reach, and where risk is likely to emerge.
See how it works Prompt injection
Tool misuse
Data leakage
Secrets exposure
Missing approvals
No audit trail
Flagship · Agentic Security Review
The sharpestplace to start
Our flagship engagement: a focused review of the execution layer before agents touch production systems.
Initial reviews can start from architecture, workflows, demos, and system descriptions. No code access is required to begin.
Review the full scope- 01
Architecture and agent workflow review
- 02
MCP and tool permission mapping
- 03
Prompt injection and data leakage risk analysis
- 04
Guardrails, human approval, and audit log assessment
- 05
Prioritized remediation plan
Best fit for teams shipping agents with
MCP integrationsInternal toolsCustomer data accessBrowser actionsWorkflow automationHuman approval paths
Review artifacts
From risk surfaceto next steps
A focused review with clear findings, evidence, and prioritized remediation.
Mochavi turns analysis into action. Clear reports. Prioritized risks. Concrete changes your team can sequence.
Turn review into engineering work
Discuss a projectAgentic Security Review Report
Focused security assessment, evidence, and recommendations for the execution layer.
Risk register
High 3 Medium 7 Low 4
Remediation plan
- Restrict tool access
- Add human approval
- Scope data permissions
- Enable audit logging
Decision support
4workstreams
Product proof
We ship what we believe.
Our point of view is easier to trust when it ships. Blobster is a product we built and maintain — and a working demonstration of how we treat sensitive data.
- Runs entirely in your browser
- No backend, telemetry, or paste URLs
- Handles production payloads and secrets safely
- Proof of how we treat sensitive data
Work with Mochavi
Have a system worth securing?
Bring us an AI agent, a sensitive production system, or a tool you need built right. We start by understanding the execution layer.
The Agentic Security Review is the sharpest place to start, and we are currently accepting a small number of pilot reviews for teams deploying agents into real workflows.
AI agentsMCP integrationsTool permissionsPrompt injectionData leakageAudit logsHuman approvalProduction readiness
See the flagship review Discuss a project