AI AGent Home & Dashboard

Inside Protos AI

A walkthrough of the platform, in the order a team actually uses it. Configure an agent, connect your integrations, align workflows to your playbooks, run investigations on-demand or scheduled, review the output, build the knowledge graph, check the audit trail.

Every investigation on Protos AI is auditable by default, and every agent operates with a human in the loop. Both are requirements carried over from the environments the product was first built for.

01 - Operations

One view of the team's work

Active agents, open investigations, hours saved, and cost per investigation — visible on one screen. When the head of CTI is asked what the team closed this month, the answer is already there.

Protos Labs Command Centre — AI agent swarm dashboard showing active agents, investigation status, and real-time operational metricsProtos Labs Create Agent — guided 4-step workflow to define, configure, and deploy an autonomous AI threat intelligence agent
Protos Labs agent creation — personalise AI agent capabilities and assign roles for cyber threat intelligence or insurance underwriting
Protos Labs agent setup — equip autonomous AI agent with OSINT tools, data sources, and investigation capabilities
Protos Labs agent deployment — review and launch configured autonomous AI threat intelligence agent

🧠 Metrics

Investigations completed, analyst hours saved, cost per investigation. Live.

🤖 Agent

Active agents, their case load, their completion rate.

🛠️ Investigations

Active, recent, and scheduled work. Owner, agent, and status, all visible.

02 - AGENT Configuration

Purpose-built agents, configured for the work.

A phishing triage agent. A fraud typology agent. A vulnerability hunt agent. Each shaped to the work, the tone, and the tools the team already uses. Four steps, no code.

Protos Labs Create Agent — guided 4-step workflow to define, configure, and deploy an autonomous AI threat intelligence agent
Protos Labs agent creation — personalise AI agent capabilities and assign roles for cyber threat intelligence or insurance underwriting
Protos Labs agent setup — equip autonomous AI agent with OSINT tools, data sources, and investigation capabilities
Protos Labs agent deployment — review and launch configured autonomous AI threat intelligence agent

🪺 Identity

Name the agent, define its purpose, assign it to a workflow.

🧠 Behaviour

Set tone, output format, and severity framing to match existing analyst playbooks.

🛠️ Tools

Equip the agent with what it needs. OSINT, SIEM queries, graph building, reporting. Nothing extra.

03 - INTEGRATIONs

Your existing stack remains. Protos sits above it.

Protos AI integrates with commercial intelligence feeds, government advisory channels, social media, and curated open-source channels — centralizing your data into a single, unified investigation workspace.

We support multiple formats such as API, STIX/TAXII, MCP, JSON, CSV, PDF and more.

Protos Labs Create Agent — guided 4-step workflow to define, configure, and deploy an autonomous AI threat intelligence agent
Protos Labs agent creation — personalise AI agent capabilities and assign roles for cyber threat intelligence or insurance underwriting
04 - Investigation Record

The record of every investigation the team has run.

Every investigation the team runs is preserved — the evidence, the reasoning, the conclusion. Ready for the regulator, the auditor, or the post-incident review, because in the environments Protos AI was built for, that readiness was not optional.

Protos Labs Investigations dashboard — monitor and manage multiple concurrent autonomous AI cyber threat intelligence investigations

📋 Full Investigation Log

Every investigation, every agent, every outcome. Searchable, filterable, exportable.

🔎 Status & Ownership

Active, complete, awaiting review. Owner and assigned agent.

💰 Resource Tracking

Token consumption per investigation, so cost per investigation is a number you can see, not a number you infer.

05 - Workspace

Where the Analyst works with the AI agent

A three-column view. The sources the agent is drawing on. The chat where the analyst directs the work. The insights the agent is producing. A review step at the top, so nothing is promoted until the analyst signs off.

Protos Labs Create Agent — guided 4-step workflow to define, configure, and deploy an autonomous AI threat intelligence agent
Protos Labs agent creation — personalise AI agent capabilities and assign roles for cyber threat intelligence or insurance underwriting
Protos Labs agent setup — equip autonomous AI agent with OSINT tools, data sources, and investigation capabilities
Protos Labs agent deployment — review and launch configured autonomous AI threat intelligence agent
Protos Labs AI investigation workspace — three-panel interface with agent activity, evidence collection, and structured intelligence findings

🔧 Connected Sources

Every file, feed, and tool the agent is pulling from — visible, searchable, and individually verifiable. The analyst can see what the agent is working with, add a source mid-investigation, or exclude one that is not appropriate.

🤖 Agent Chat

The conversation between the analyst and the agent. Objective, clarifying questions, proposed steps, and back-and-forth as the work progresses. A Fast or Deep mode, depending on whether the analyst wants a quick answer or a thorough one.

📁 Insights

The structured output the agent is building — the objective as interpreted, the investigation plan with progress tracked, the findings ranked by severity, and the draft report. Overview, Evidence, and Graph views, depending on how the analyst wants to see it.

👁️ Review & Promote

Findings sit in a Pending Review state until the analyst reviews them. Nothing is promoted to the AI's memory without that sign-off.

05 - workspace : overview & findings

Investigation Objective, Plan & Structured Findings

The Overview panel shows the investigation objective, a step-by-step investigation plan with progress tracking, the final report, and structured findings sorted by severity.

Protos Labs workspace overview — AI-generated investigation objective, plan, and structured findings summaryProtos Labs investigation overview panel — structured findings with evidence links, threat categories, and recommended actions
Protos Labs findings panel — AI-categorised threat intelligence findings with severity ratings and supporting evidenceProtos Labs investigation results — detailed threat findings with supporting evidence and actionable intelligence

🎯 Investigation Objective

The full investigation brief at the top — including the target (KONNI APT), scope (deep-dive analysis), and specific deliverables requested.

📋 Investigation Plan

A 7-step plan with real-time progress tracking (1/7 complete). Each step maps to a subagent phase: collection, analysis, graph building, reporting.

🔴 Severity-Ranked Findings

Structured findings sorted by severity (High/Medium/Low) with category tags — Threat Actor, Infrastructure, Operational — for immediate triage.

06 - Knowledge graph

Every investigation deepens the AI's memory.

Most tools produce reports that are read once and filed. Protos AI builds a graph. Every entity, every relationship, every conclusion — carried forward across every investigation the team has run.

Protos Labs knowledge graph — interactive force-directed visualisation of threat entities, attack infrastructure, and entity relationships built from AI investigationsProtos Labs threat intelligence graph — interconnected view of threat actors, infrastructure, and attack pathwaysProtos Labs organisational intelligence memory — persistent knowledge layer showing cumulative entity relationships and threat intelligence across all investigations

🔍 Entities

IP addresses, domains, malware, actors, vendors, identities. Extracted automatically, deduplicated, confidence-scored.

📍 Relationships

Every node carries its evidence and its confidence. No opaque attribution. Manually adjust the confidence to promote it to memory.

🗺️ Patterns

Campaign clusters, shared infrastructure, recurring techniques — visible across investigations, analysts, and time.

07 - WORKFLOWs

From Manual to AI -Driven Workflows

Every mature team has playbooks. The IOC enrichment sequence. The fraud escalation flow. The vendor compromise response. Protos AI runs them — step by step, with the team's customisations intact.

Protos Labs workspace overview — AI-generated investigation objective, plan, and structured findings summaryProtos Labs investigation overview panel — structured findings with evidence links, threat categories, and recommended actions
Protos Labs findings panel — AI-categorised threat intelligence findings with severity ratings and supporting evidenceProtos Labs investigation results — detailed threat findings with supporting evidence and actionable intelligence
1
Input Indicator
2
IOC Enrichment
3
Infrastructure Recon
4
Vulnerability Correlation
5
SIEM Query
6
Threat Hunting
7
Graph Build
8
Report Generation
9
Alert Dissemination
10
Ticket Creation

🔨 Upload Existing Playbooks

Word, Confluence, Jira. Parsed into executable workflows.

📤 Build new ones in-platform

No code. No data science team required.

🚪Customise every step

Tools, instructions, approval gates. The playbook remains the specification.

★ START FOR FREE

Experience Protos AI Yourself

Free access to the cyber agent, with open-source intelligence and the full agent capability. Sample the product before any broader conversation.  

Learn what Protos AI comes with below.   

Sign Up for Freemium

★ Compare TIERS

Freemium vs Enterprise

Pick the tier that fits where you are today. Upgrade when you need to scale.

Freemium

Get Started for Free

No credit card required

For individual analysts who want to start running AI-powered investigations immediately — no setup, no time limit.

Individual investigations — ad-hoc, on demand

OSINT & public intelligence sources — automatically queried

Core investigation tools — full toolkit access

Limited monthly token budget — enough for regular use

Standard investigation reports — auto-generated output

Default AI model — no configuration needed

1 analyst seat — Workspace V2 command center

Basic authentication + community support
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First investigation brief in under 1 hour

CapabilityFreemiumEnterprise
Usage & Investigations
Primary use caseWhat this plan is built forIndividual investigationsShared investigations & team workspace
UsersSingle userMulti-user teams
Token usageMonthly AI compute budgetLimited monthly tokens~20× higher token capacity
Usage & Investigations
Data Sources & Integrations
Intelligence sourcesData feeds queried per investigationOSINT & public intelligence sourcesOSINT + commercial feeds + enterprise tool integrations
Workflow customizationBasic workflow templatesCustom investigation workflows
API accessProgrammatic platform accessFull API access
AI Model & Agent Capabilities
Model supportLLM powering investigationsDefault modelMulti-LLM support
AI Model & Agent Capabilities
Model supportLLM powering investigationsDefault modelMulti-LLM support
Bring Your Own Model / API KeysSupported
AI skills & agent customizationCustom agent logic and skill setsCustom AI skills and agents
Infrastructure & Security
EnvironmentShared platformDedicated environment
Data isolationShared environmentDedicated data isolation
Security & access controlBasic authenticationEnterprise RBAC & identity integration
Audit trailFull investigation audit logs
Reporting & Support
Investigation reportingStandard investigation reportsCustomizable intelligence reports
SupportCommunity / basicDedicated support