For Enterprise Organizations

Knowledge SilosKill Enterprise Velocity

100+ engineers. Dozens of services. One source of truth. Probe gives enterprise teams unified code intelligence across your entire organization — at scale.

Enterprise scaleSOC 2 compliantOn-premSSO & RBAC

Trusted by engineering teams managing 10M+ lines of code.

What changes for your organization
Before
6-8 weeks to onboard senior engineers
Knowledge trapped in 3-5 key people
Cross-team dependencies block releases
After
First meaningful commit in 1-2 weeks
Institutional knowledge in searchable AI
Impact analysis before every change
Enterprise-ready by design
SOC 2 SSO & RBAC On-prem

Why enterprises choose Probe

System-Wide Understanding

Query across every service, every team, every repository. One unified view of your entire architecture and how it all connects.

Enterprise Security

SOC 2 compliant, SSO integration, role-based access control, full audit trails. Deploy on-prem or in your private cloud.

Accelerate Onboarding

New hires productive in weeks, not months. Self-serve access to architectural context, ownership, and historical decisions.

De-Risk Changes

Understand blast radius before deploying. Cross-team dependency analysis prevents cascading failures and production incidents.

The Real Problem

Your codebase grew faster than your ability to understand it.

At enterprise scale, knowledge fragmentation isn't a nuisance. It's a strategic liability that compounds every quarter.

01

The Talent Trap

Three senior engineers hold the keys to critical systems. They answer questions all day instead of building. When one leaves, you lose years of institutional knowledge overnight. You can't scale expertise fast enough to match headcount growth.

02

The Coordination Tax

Payment team wants to refactor the billing service. Needs sign-off from Platform, Security, and three other teams who depend on it. Two weeks of Slack messages and meetings to understand blast radius. The actual change takes 3 days. The coordination took 20.

03

The Compliance Nightmare

Auditor asks: "Show me every place customer PII is stored and how it's encrypted." You know it's in 12+ services across 40+ repositories. Finding every instance takes a team 2 weeks. The actual audit question took 10 minutes. Your inability to answer it cost you a quarter's worth of engineering time.

What enterprise teams actually ask Probe

Real questions from CTOs, VPs of Engineering, and senior technical leaders running 100+ person engineering orgs.

Question
Map every service that touches customer PII, how it's encrypted at rest, and which teams own each one
Found 14 services handling PII across 6 teams. Encrypted at rest: billing-service (AES-256, owned by Payments), user-profile-service (AES-256, owned by Identity), analytics-warehouse (not encrypted, owned by Data — flagged for remediation). Full breakdown: auth-service encrypts SSNs via KMS in auth/models/user.go, order-history stores addresses encrypted...
Investigation
We're planning to deprecate the legacy-payments API. Which internal services and external partners still depend on it?
Legacy-payments API has 8 internal consumers and 3 external partner integrations. Internal: billing-service (critical path), subscription-manager (can migrate), invoice-generator (low volume). External partners: Acme Corp (contract until Q3), Beta Systems (deprecated integration, can remove), Gamma Inc (active, needs 6-week migration notice per contract). Migration blockers: billing-service needs refactor first, estimated 4 weeks...
Question
Show me architectural patterns that the Platform team recommends vs what teams are actually implementing
Platform team standard (docs/architecture/service-template.md): circuit breakers via Resilience4j, structured logging with correlation IDs, health checks at /actuator/health. Reality: 12/18 services follow the standard. Deviations: legacy-api uses raw HttpClient (no circuit breaker), analytics-worker uses println debugging (no structured logging), notification-service has no health check endpoint...
Question
If the Redis cluster goes down, which services fail immediately vs gracefully degrade?
Redis outage impact analysis: Immediate failure (no fallback): session-manager, rate-limiter, feature-flags-service (6 services). Graceful degradation (with fallback): cart-service (falls back to DB), recommendation-engine (serves stale cache). Unknown behavior (needs code review): legacy-api, analytics-ingest. Blast radius: ~40% of API endpoints would return 503...
Investigation
Compliance needs a report: every place we call external APIs, what data we send, and whether we log request/response payloads
Found 23 external API calls across 11 services. Data sent includes: customer emails (4 services), payment tokens (2 services), order details (3 services). Logging behavior: 8 services log full request/response (PII risk), 7 services log headers only (compliant), 8 services have no logging (audit gap). High risk: payment-processor logs full CC tokens in payment-processor/lib/stripe.go line 47...
Digest
Which teams have the most cross-team dependencies? Who should be in our architecture review meetings?
Cross-team dependency analysis: Platform team (18 downstream consumers, highest impact). Payments team (12 consumers, second highest). Identity team (9 consumers). Recommendation: Platform and Payments should have standing seats in architecture reviews. Identity team should join for auth/user-related changes. Data team has fewest dependencies (mostly consumers, not providers)...
Question
Map every service that touches customer PII, how it's encrypted at rest, and which teams own each one
Found 14 services handling PII across 6 teams. Encrypted at rest: billing-service (AES-256, owned by Payments), user-profile-service (AES-256, owned by Identity), analytics-warehouse (not encrypted, owned by Data — flagged for remediation). Full breakdown: auth-service encrypts SSNs via KMS in auth/models/user.go, order-history stores addresses encrypted...
Investigation
We're planning to deprecate the legacy-payments API. Which internal services and external partners still depend on it?
Legacy-payments API has 8 internal consumers and 3 external partner integrations. Internal: billing-service (critical path), subscription-manager (can migrate), invoice-generator (low volume). External partners: Acme Corp (contract until Q3), Beta Systems (deprecated integration, can remove), Gamma Inc (active, needs 6-week migration notice per contract). Migration blockers: billing-service needs refactor first, estimated 4 weeks...
Question
Show me architectural patterns that the Platform team recommends vs what teams are actually implementing
Platform team standard (docs/architecture/service-template.md): circuit breakers via Resilience4j, structured logging with correlation IDs, health checks at /actuator/health. Reality: 12/18 services follow the standard. Deviations: legacy-api uses raw HttpClient (no circuit breaker), analytics-worker uses println debugging (no structured logging), notification-service has no health check endpoint...
Question
If the Redis cluster goes down, which services fail immediately vs gracefully degrade?
Redis outage impact analysis: Immediate failure (no fallback): session-manager, rate-limiter, feature-flags-service (6 services). Graceful degradation (with fallback): cart-service (falls back to DB), recommendation-engine (serves stale cache). Unknown behavior (needs code review): legacy-api, analytics-ingest. Blast radius: ~40% of API endpoints would return 503...
Investigation
Compliance needs a report: every place we call external APIs, what data we send, and whether we log request/response payloads
Found 23 external API calls across 11 services. Data sent includes: customer emails (4 services), payment tokens (2 services), order details (3 services). Logging behavior: 8 services log full request/response (PII risk), 7 services log headers only (compliant), 8 services have no logging (audit gap). High risk: payment-processor logs full CC tokens in payment-processor/lib/stripe.go line 47...
Digest
Which teams have the most cross-team dependencies? Who should be in our architecture review meetings?
Cross-team dependency analysis: Platform team (18 downstream consumers, highest impact). Payments team (12 consumers, second highest). Identity team (9 consumers). Recommendation: Platform and Payments should have standing seats in architecture reviews. Identity team should join for auth/user-related changes. Data team has fewest dependencies (mostly consumers, not providers)...
Automation
@Probe weekly: generate a report of services with security vulnerabilities, who owns them, and which have been open longer than 30 days. Post to #security-alerts.
Weekly security scan complete. 7 services with CVEs: auth-gateway (CVE-2024-1234, owned by Platform team, open 45 days — escalate), billing-service (CVE-2024-5678, owned by Payments, open 12 days — on track), user-api (CVE-2024-9012, owned by Identity, open 67 days — SLA breach). Full report with remediation links posted to #security-alerts. Created Jira tickets for SLA breaches.
Automation
@Probe on every cross-team PR: identify which teams need to review based on service dependencies and ownership. Auto-tag them.
PR #1847 from @alice (Payments team) modifies billing-service API contract. Dependency analysis: cart-service (Shopping team), subscription-manager (Growth team), invoice-generator (Finance team) all call this API. Auto-tagged: @shopping-team-lead @growth-team-lead @finance-team-lead for required review. Breaking changes detected in billing/api/v2/charge.go — flagged as HIGH PRIORITY review needed.
Automation
When an engineer leaves, audit which services they were the primary owner of and which need new owners assigned
@bob left the organization. Primary owner of: legacy-api (last commit 3 months ago, low activity), auth-gateway (actively developed, NEEDS URGENT REASSIGNMENT), feature-flags-service (shared ownership with @charlie, covered). Secondary contributor to: billing-service, user-profile-service. Created PLAT-1203: Reassign auth-gateway ownership. Notified @eng-leadership via Slack.
Automation
Before every quarterly planning cycle: generate technical debt report by team — how many TODOs, deprecated dependencies, and missing tests
Q2 2024 Technical Debt Report: Platform team (34 TODOs, 2 deprecated deps, 78% test coverage). Payments team (67 TODOs, 5 deprecated deps, 65% test coverage — below target). Identity team (12 TODOs, 0 deprecated deps, 92% coverage — best in class). Highest priority: Payments team using Spring Boot 2.x (EOL April 2024). Full report with cost estimates posted to #eng-leadership.
Investigation
Incident post-mortem: payment processing was down for 37 minutes. Trace the blast radius and find every impacted customer-facing feature.
Payment processing outage (14:23 to 15:00 UTC). Direct impact: checkout flow, subscription renewals, invoice generation (all blocked). Indirect impact: order history (read-only degraded), recommendation engine (payment-based recommendations failed silently). Customer-facing features affected: 8 web pages, 4 API endpoints, 2 mobile app screens. Estimated user impact: ~12,000 attempted transactions failed. Root cause: billing-service DB connection pool exhausted...
Automation
Nightly: scan for hardcoded secrets, API keys, and credentials across all repositories. Alert security team immediately if found.
Nightly secrets scan complete. ALERT: found AWS access key in analytics-pipeline/config/prod.yml committed by @dave 14 hours ago (commit abc123). Slack DM sent to @dave and @security-team. Created incident INC-8821. Recommended actions: rotate key immediately, add to .gitignore, move to secrets manager. Also found: 3 localhost connection strings (low risk), 1 test API key (safe).
Automation
@Probe weekly: generate a report of services with security vulnerabilities, who owns them, and which have been open longer than 30 days. Post to #security-alerts.
Weekly security scan complete. 7 services with CVEs: auth-gateway (CVE-2024-1234, owned by Platform team, open 45 days — escalate), billing-service (CVE-2024-5678, owned by Payments, open 12 days — on track), user-api (CVE-2024-9012, owned by Identity, open 67 days — SLA breach). Full report with remediation links posted to #security-alerts. Created Jira tickets for SLA breaches.
Automation
@Probe on every cross-team PR: identify which teams need to review based on service dependencies and ownership. Auto-tag them.
PR #1847 from @alice (Payments team) modifies billing-service API contract. Dependency analysis: cart-service (Shopping team), subscription-manager (Growth team), invoice-generator (Finance team) all call this API. Auto-tagged: @shopping-team-lead @growth-team-lead @finance-team-lead for required review. Breaking changes detected in billing/api/v2/charge.go — flagged as HIGH PRIORITY review needed.
Automation
When an engineer leaves, audit which services they were the primary owner of and which need new owners assigned
@bob left the organization. Primary owner of: legacy-api (last commit 3 months ago, low activity), auth-gateway (actively developed, NEEDS URGENT REASSIGNMENT), feature-flags-service (shared ownership with @charlie, covered). Secondary contributor to: billing-service, user-profile-service. Created PLAT-1203: Reassign auth-gateway ownership. Notified @eng-leadership via Slack.
Automation
Before every quarterly planning cycle: generate technical debt report by team — how many TODOs, deprecated dependencies, and missing tests
Q2 2024 Technical Debt Report: Platform team (34 TODOs, 2 deprecated deps, 78% test coverage). Payments team (67 TODOs, 5 deprecated deps, 65% test coverage — below target). Identity team (12 TODOs, 0 deprecated deps, 92% coverage — best in class). Highest priority: Payments team using Spring Boot 2.x (EOL April 2024). Full report with cost estimates posted to #eng-leadership.
Investigation
Incident post-mortem: payment processing was down for 37 minutes. Trace the blast radius and find every impacted customer-facing feature.
Payment processing outage (14:23 to 15:00 UTC). Direct impact: checkout flow, subscription renewals, invoice generation (all blocked). Indirect impact: order history (read-only degraded), recommendation engine (payment-based recommendations failed silently). Customer-facing features affected: 8 web pages, 4 API endpoints, 2 mobile app screens. Estimated user impact: ~12,000 attempted transactions failed. Root cause: billing-service DB connection pool exhausted...
Automation
Nightly: scan for hardcoded secrets, API keys, and credentials across all repositories. Alert security team immediately if found.
Nightly secrets scan complete. ALERT: found AWS access key in analytics-pipeline/config/prod.yml committed by @dave 14 hours ago (commit abc123). Slack DM sent to @dave and @security-team. Created incident INC-8821. Recommended actions: rotate key immediately, add to .gitignore, move to secrets manager. Also found: 3 localhost connection strings (low risk), 1 test API key (safe).

Three things that change everything

01

Unified Code Intelligence Across All Teams

Query your entire codebase — every service, every team, every repository — as if it were one system.

  • "Which services handle customer payment data and how is it encrypted?"
  • "Show me every API endpoint that depends on the auth-service"
  • "What's the blast radius if we take down the Redis cluster?"
  • "Map the full request path from API gateway to database for /checkout"

Most enterprises have knowledge fragmented across teams, Confluence pages that are 6 months stale, and Slack channels where context gets lost. Probe treats your entire codebase as the single source of truth. It reads code semantically across all repositories, understands cross-service dependencies, and connects dots between teams that don't even know they depend on each other.

Multi-team architectureQuery across all teams and services in one question, no manual stitching
Cross-org dependency mappingUnderstand which teams depend on which services before you make changes
Historical contextSee why decisions were made, who made them, and what constraints existed
02

Enterprise-Grade Compliance & Security

Know where sensitive data lives, how it's protected, and prove it to auditors in minutes instead of weeks.

Compliance at enterprise scale is a nightmare because the answers live in code that's scattered across 50 repositories and 10 teams. When the auditor asks "show me everywhere you store PII," you can't grep your way to an answer. You need semantic understanding of data flow across your entire architecture.

Probe maps data lineage across your system. It finds every service that touches customer PII, traces how it moves between teams, identifies where encryption is missing, and generates compliance reports automatically. When regulatory requirements change, you know exactly what code needs to be updated and which teams own it.

Data lineage trackingTrace PII, payment data, and sensitive information across all services
Security policy enforcementDetect unencrypted data, missing access controls, and security anti-patterns
Audit trail generationAutomatic reports for SOC 2, HIPAA, PCI-DSS, and custom compliance frameworks
03

Accelerated Onboarding at Scale

New engineers productive in weeks, not months. Self-serve access to institutional knowledge without pulling senior engineers into endless meetings.

At 100+ engineers, onboarding isn't a people problem, it's a knowledge distribution problem. Your senior engineers spend 30% of their time answering architecture questions instead of building. New hires take 8 weeks to make their first meaningful contribution because understanding the system requires tribal knowledge that isn't written down.

Probe gives every engineer — new or experienced — the same level of system understanding. It answers architectural questions instantly, shows historical context for why decisions were made, and guides engineers to the right code without waiting on Slack responses. Senior engineers stop being human documentation. New hires ramp up 3x faster.

Self-serve architecture explorationEngineers get answers from code, not from interrupting senior staff
Automated onboarding guidesGenerate team-specific, role-specific context from actual codebase reality
Institutional knowledge capturePreserve why decisions were made and what constraints existed at the time

Workflow packs for enterprise operations

Production-tested workflows designed for large engineering organizations. Deploy immediately, customize to your org structure, evolve over time.

Onboarding

New Hire Acceleration

Automatically generate personalized onboarding guides based on the engineer's role, team, and service ownership. Include architecture context, key dependencies, and historical decisions without pulling senior engineers into meetings.

  • Role-specific architecture overview
  • Team service ownership map
  • Key dependencies and integration points
  • Historical decision context
Compliance

Automated Audit Preparation

Generate compliance reports on demand: where PII lives, how it's encrypted, which teams own it, and which controls are in place. Answer auditor questions in minutes instead of assigning a team for 2 weeks.

  • PII and sensitive data mapping
  • Encryption status report
  • Access control audit
  • Team ownership and SLA tracking
Cross-Team

Dependency Impact Analysis

Before any major change, understand blast radius automatically. See which teams depend on your service, what will break, and who needs to approve. Turn 2-week coordination cycles into automated pre-flight checks.

  • Downstream consumer identification
  • Breaking change detection
  • Auto-tag impacted team leads
  • Migration path recommendation
Operational

Incident Context Assembly

When production breaks, give on-call engineers full context immediately: what changed recently, which teams are affected, what the blast radius is, and what similar incidents looked like. Cut MTTR by eliminating context-gathering overhead.

  • Recent change timeline
  • Blast radius analysis
  • Related past incidents
  • Team escalation paths

Built for enterprise security and compliance

SOC 2 Type II Compliant

Full SOC 2 Type II compliance. Annual audits, penetration testing, and security certifications maintained continuously. Meet your enterprise security requirements out of the box.

On-Premises Deployment

Deploy entirely on-prem or in your private cloud. Code never leaves your infrastructure. Air-gapped deployment capable. Full data sovereignty and compliance with regional data residency requirements.

SSO & RBAC

Enterprise SSO integration (Okta, Azure AD, Google Workspace). Role-based access control at team and repository level. Audit logs for every query and action. Meets enterprise identity requirements.

OpenTelemetry Observability

Full OpenTelemetry instrumentation on every workflow, query, and AI interaction. Export to your existing Datadog, Splunk, or Grafana stack. Debug AI workflows like any other production system.

Open Source vs Enterprise

Start with the open-source core to validate the technology on a single team. Scale to enterprise when you need multi-team coordination and compliance features.

Probe Open Source

Free forever

The core code intelligence engine. Perfect for individual teams evaluating the technology on their own repositories before rolling out org-wide.

  • Single-team code understanding — Query one team's repositories at a time
  • Semantic code search — Understands code structure, not just text matching
  • No indexing required — Works instantly on any codebase, runs locally
  • MCP integration — Use with Claude Code, Cursor, or any MCP-compatible tool
  • Any LLM provider — Claude, GPT, open-source models — your choice
  • Privacy-first — Everything runs locally, no data sent to external servers

Probe Enterprise

Contact for pricing

Everything in Open Source, plus multi-team coordination, compliance automation, and enterprise security features for organizations with 100+ engineers.

  • Multi-team architecture — Query across all teams, services, and repositories in your organization
  • Cross-org dependency mapping — Understand how teams and services depend on each other
  • Compliance automation — PII mapping, encryption audits, access control reports for SOC 2, HIPAA, PCI-DSS
  • SSO & RBAC — Enterprise identity integration with team-level and repo-level permissions
  • Jira & Confluence integration — Connect code context with project management and documentation
  • Workflow automation — Pre-built workflows for onboarding, compliance, incident response
  • Blast radius analysis — Understand impact before you make cross-team changes
  • Security scanning — Detect hardcoded secrets, unencrypted PII, and policy violations
  • Slack/Teams integration — Enterprise-wide access to code intelligence where teams already work
  • On-premises deployment — Air-gapped capable, full data sovereignty, SOC 2 Type II compliant

How to evaluate Probe at enterprise scale

We recommend starting with a single team pilot to validate ROI, then rolling out org-wide once you see measurable impact on velocity and compliance overhead.

Phase 1

Technical Validation

~10 minutes

Start with the open-source version. Have a single team validate the core technology before committing to an enterprise rollout.

~2 min

Add to AI Coding Tools

Give one team's engineers code intelligence in their existing tools. Works with Claude Code, Cursor, or any MCP-compatible editor. See if it reduces the number of Slack questions to senior engineers.

You get: A pilot team using AI that understands your actual architecture. Measure reduction in "how does this work?" Slack messages to determine if it's worth scaling.
AI code editor setup →
~5 min

Automate PR Reviews

Add a GitHub Action for one team's repo to see automated code review in action. Every PR gets security, compliance, and architectural feedback before human review.

You get: Data on how many issues are caught pre-review. Measure reduction in review cycles and time-to-merge to determine ROI before org-wide rollout.
~10 min

Deploy Team-Specific Slack Bot

Create a Slack bot for one team's channel. Engineers ask architectural questions and get answers grounded in actual code. Measure reduction in interruptions to senior staff.

You get: Quantifiable data on how many questions are answered self-serve vs escalated to humans. Use this to project ROI at org scale.
Full setup guide →
Phase 2

Enterprise Pilot

4-6 weeks

Once you've validated core technology with one team, run an enterprise pilot across 3-5 teams to test multi-team coordination, compliance workflows, and cross-org dependency mapping.

1
Select pilot teams

Choose 3-5 teams with high interdependencies and frequent cross-team coordination pain. Ideal candidates: teams that ship slowly due to cross-team approvals or struggle with onboarding new engineers.

2
Map your org architecture

We work with your architects to connect all pilot team repositories, map cross-team dependencies, and configure team-level access controls. This session usually takes 2-4 hours.

3
Deploy enterprise workflows

Set up compliance automation, dependency impact analysis, and onboarding workflows. Connect to your SSO, Jira, and Slack. Configure OpenTelemetry export to your monitoring stack.

4
Measure impact

Track onboarding time for new hires, cross-team coordination overhead, compliance report generation time, and Slack question volume to senior engineers. Compare to pre-pilot baselines.

Success criteria: 50% reduction in onboarding time, 70% reduction in cross-team coordination overhead, 90% reduction in compliance report preparation time. Measurable decrease in "human search engine" load on senior staff.

Want to discuss how an enterprise pilot would work for your organization?

Schedule a Leadership Discussion

What enterprise leaders ask us

How does this differ from Copilot or other AI coding tools?

Copilot and ChatGPT work on whatever code is in front of them. They don't understand your multi-team architecture, cross-service dependencies, or organizational context. They can't tell you which teams need to approve a change or how a service failure cascades across your system.

Probe understands your entire enterprise codebase — all teams, all services, all repositories — as a unified system. It answers questions that require cross-team knowledge and organizational context that generic AI tools can't access.

What about data security and compliance?

Probe is SOC 2 Type II compliant and can be deployed entirely on-premises or in your private cloud. Code never leaves your infrastructure. We support air-gapped deployments for maximum security. SSO integration with RBAC ensures only authorized users access specific repositories. Full audit trails for every query meet compliance requirements.

How long does enterprise deployment take?

Initial pilot with 3-5 teams: 4-6 weeks including architecture mapping, SSO integration, and workflow configuration. Org-wide rollout after successful pilot: 8-12 weeks depending on number of teams and repositories. Most enterprises see ROI within the pilot phase from reduced coordination overhead alone.

What's the ROI for an enterprise our size?

Enterprises with 100+ engineers typically see: 50% reduction in onboarding time (6-8 weeks down to 2-3 weeks), 70% reduction in cross-team coordination overhead (coordination cycles from weeks to days), 90% reduction in compliance report preparation (weeks of work down to hours), and 30% reduction in senior engineer interruptions (they build instead of answering questions). Most organizations hit positive ROI within 3-6 months.

Ready to scale code intelligence across your organization?

Let's discuss how Probe can reduce coordination overhead, accelerate onboarding, and automate compliance for your enterprise. We'll show you how it works on your architecture.