RADLAB LLC
Bourdon, built by RADLAB LLC, is a memory federation system that enables multiple AI agents (Claude, Codex, Cursor, Copilot, Devin, Gemini, Hermes, GitLab) to share a single persistent knowledge store without latency delays. It uses recognition-first recall to let agents respond instantly while hydrating memory details in the background, and supports per-agent tokens and trust tiers for granular access control. Agencies can deploy Bourdon on client infrastructure for free or use managed hosting at $12/seat/month with per-tenant isolation and backups. The append-only audit log creates a complete history of agent learning, critical for compliance and debugging multi-agent workflows. Purpose-built for AI development agencies and technical teams managing agent fleets, not for general-purpose client retainers.
RADLAB LLC is an agent memory knowledge connector platform, priced at $12/seat/month on the Hosted Managed plan, integrating with Claude, Codex, Cursor, and Copilot. InnovaAI scores it 5.1/10 for agency resale.
Agency Audit
Bourdon is a memory federation layer that lets multiple AI agents (Claude, Codex, Cursor, Copilot, Devin, Gemini) share persistent context without latency, built by RADLAB LLC. It's purpose-built for AI development agencies and teams running multi-agent workflows where knowledge learned by one agent must be instantly available to others across accounts and machines. The recognition-first architecture reduces recall latency to near zero, enabling agents to respond immediately while hydrating details in the background. Agencies reselling this to clients would position it as infrastructure for scaling AI agent deployments, not as a client-facing tool. Best fit: technical teams building internal AI agent fleets, not general-purpose client retainers.
5.1/10
58%
2d 1-2 days
- You build multi-agent AI workflows for clients and need those agents to share learned context across Claude, Codex, and Cursor without separate memory systems for each tool.
- Your clients run internal AI agent fleets and require append-only audit logs for compliance or operational transparency.
- You want to offer a self-hostable memory layer so clients can run Bourdon on their own infrastructure without vendor lock-in.
- Your clients are non-technical and expect a plug-and-play tool; Bourdon requires understanding AI agent architecture and memory federation concepts.
- You need a white-label client portal or branded dashboard; Bourdon's client-facing surfaces display RADLAB LLC branding.
- Your clients require HIPAA compliance immediately; HIPAA BAA is only available on the Enterprise plan, which requires custom pricing and a sales conversation.
Profit Path
$12/mo
$1K–$3K/project
Monthly Recurring
Planning benchmark at United States price levels. Not a measured market survey.
Platform Features
Core capabilities of RADLAB LLC
Federated memory across agent fleet
Multiple AI agents (Claude, Codex, Cursor, Copilot, Devin, Gemini) share a single memory store, so facts learned by one agent are instantly recognized by others across accounts and machines. Eliminates duplicate context management and ensures consistency across your agent fleet.
Recognition-first recall with near-zero latency
Bourdon prioritizes context recognition over search, reducing recall latency to near zero milliseconds. Agents respond immediately while memory details hydrate in the background, improving user experience in real-time agent interactions.
Self-hostable runtime at no cost
Deploy Bourdon's memory engine on your own infrastructure for free, giving clients full control over data residency and compliance. Managed hosting ($12/seat/month) is available for agencies that prefer RADLAB LLC to handle infrastructure.
Per-agent tokens and trust tiers
Assign granular access controls so different agents or client teams can only retrieve memory relevant to their role or scope. Prevents unauthorized context leakage and enforces least-privilege memory access.
Append-only audit log
Every memory write is immutable and logged, creating a complete history of what each agent learned and when. Critical for compliance audits, debugging multi-agent workflows, and understanding how client AI systems evolved over time.
Agent adapters for major AI platforms
Native connectors for Claude, Codex, Cursor, Copilot, Devin, Gemini, Hermes, and GitLab reduce integration work. Agencies can wire up new agents without custom API code.
What Makes RADLAB LLC Different
Unique advantages vs similar tools in this niche
Recognition-first retrieval reduces recall latency to 0 ms
vs Traditional search-based memory systems with ~406 ms latencyBourdon recognizes context instantly and hydrates details in the background, unlike search-first approaches.
Cross-agent federation is included at the free tier
vs Competitors that gate federation behind paid tiersFederation is never gated; cross-agent memory is the product, not an upsell.
Self-hosting is the default and the whole engine
vs Cloud-only memory solutionsYou can run the full engine on your own box, with no features held back.
Investment ROI Calculator
Value equation analysis for RADLAB LLC, based on the Hormozi framework
What is the Hormozi framework? A four-factor score: (what the service delivers × how reliably it delivers) divided by (how long it takes × how much effort it requires). A higher Value Multiplier means a better return on the time and money invested: faster, easier, and more proven results.
2.3× value multiple: invest $12/mo and agencies typically charge $1K–$3K/project for the work it powers.
Why This Succeeds
Higher is betterClient Results Potential
What your clients actually get
Meaningful improvements: delivers clear, demonstrable value to clients
Recognition fires first. The details arrive while it’s already answering, memory in human order.
Reliability Score
How consistently this delivers results
Early-stage track record: validate with a small pilot first
Three field tests on live agents against real work.
Implementation Challenges
Lower is betterTime to First Revenue
How long until you can start earning
Standard ramp-up: accelerate to 1 day with Academy SOPs
Expect a few days from signup to first client delivery
Setup Effort
What it takes to get running
Near-turnkey: minimal setup before you can sell
Moderate effort: standard configuration with some customization needed
Viable opportunity. RADLAB LLC returns 2.3× on investment. Focus on the highest-margin service packages to maximize return.
Pricing
RADLAB LLC platform cost to your agency
Hosted Managed: $12/mo
Hosted Managed
- always-on hosting, backups, and per-tenant isolation
- the same engine as self-host, federation and graph memory included
Enterprise
- SSO / SAML, BYOC and BYOK, long audit-retention windows
- HIPAA BAA and a dedicated support channel
- built on the same self-hostable core, so a review runs against infra you control
No verified white-label program for RADLAB LLC: client-facing delivery runs under the platform's native branding.
Market Intelligence
How agencies monetize RADLAB LLC: real offer economics and market positioning
- AI development agencies
- Agencies building multi-agent workflows
- Technical teams managing AI agent fleets
- Non-technical agencies
- Agencies without AI agent usage
Project-Based
ai-toolsAgency charges per-project fee for implementation. Ongoing optimization as optional retainer.
Offer Economics: What You Charge vs. What It Costs
Margin includes platform cost + agency labor at $75/hr. Per-seat platform scales with client count.
Solo practitioners or local service businesses deploying their first AI assistant and needing persistent context across sessions
Funded startups or regional brands running multiple AI tools (Claude, Codex, Cursor) who need shared memory across their agent stack
Mid-market companies with 50–500 employees operating multi-department AI agent programs requiring centralized, low-latency shared memory
Fortune 5000 or large enterprise organizations standardizing persistent shared memory across a fleet of 20+ AI agents spanning multiple business units
Scale Economics: Based on Starter Offer
Using RADLAB LLC Starter Memory Setup at $1.8K/client. Platform: $12/mo × 1 seat(s) per client. Labor: 4h/client × $75/hr.
Net = MRR - platform cost - labor (4h/client × $75/hr). Platform scales with seat count per client.
Investment Decision Framework
Strategic vetting analysis for RADLAB LLC
Consider
Favorable fit, worth a closer look
Buy If
4You build multi-agent AI workflows for clients and need those agents to share learned context across Claude, Codex, and Cursor without separate memory systems for each tool.
Your clients run internal AI agent fleets and require append-only audit logs for compliance or operational transparency.
You want to offer a self-hostable memory layer so clients can run Bourdon on their own infrastructure without vendor lock-in.
You need per-agent tokens and trust tiers to isolate memory access across different client teams or agent roles.
Skip If
4Your clients are non-technical and expect a plug-and-play tool; Bourdon requires understanding AI agent architecture and memory federation concepts.
You need a white-label client portal or branded dashboard; Bourdon's client-facing surfaces display RADLAB LLC branding.
Your clients require HIPAA compliance immediately; HIPAA BAA is only available on the Enterprise plan, which requires custom pricing and a sales conversation.
You want a tool with zero setup overhead; federated memory systems require schema design and agent adapter configuration per client.
Bottom Line
Bourdon is a memory federation layer that lets multiple AI agents (Claude, Codex, Cursor, Copilot, Devin, Gemini) share persistent context without latency, built by RADLAB LLC. It's purpose-built for AI development agencies and teams running multi-agent workflows where knowledge learned by one agent must be instantly available to others across accounts and machines. The recognition-first architecture reduces recall latency to near zero, enabling agents to respond immediately while hydrating details in the background. Agencies reselling this to clients would position it as infrastructure for scaling AI agent deployments, not as a client-facing tool. Best fit: technical teams building internal AI agent fleets, not general-purpose client retainers.
Reality Check
Bourdon requires agencies to manage agent integrations and memory schema design for each client, adding operational overhead beyond the platform itself. Self-hosting is free but demands infrastructure management; managed hosting at $12/seat/month shifts that burden but locks clients into RADLAB LLC's infrastructure. Enterprise features (SSO, BYOC, BYOK) require custom pricing and sales cycles, limiting rapid client onboarding.
Moderate effort: standard configuration with some customization needed
Academy for RADLAB LLC
Work through it in order: the course for this service first, then the modules behind it.
No Academy modules are published for this service yet. Browse the full Academy
Core concepts
The mental model you need to price and scope the work.
- Memory Portability PremiumConcept
Memory Portability Premium is the principle that an agent memory layer is worth more to an agency when its contents can be exported, re-indexed, and replayed somewhere else. Persistent memory compounds: every client architecture decision, brand rule, and debugging discovery an agent stores makes the next session cheaper to run. But that compounding only belongs to the agency if the store is portable. A memory layer that holds context in a proprietary index converts institutional knowledge into a hostage; switching tools means re-teaching every agent what the last one already knew. The premium is the delta between a memory layer you can walk away from and one you cannot. Knownbase organizes notes by project and tag, which makes bulk export tractable, while Bourdon federates one memory across Claude, Codex, and Cursor accounts, so the same fact survives a tool swap. Audit export format before you audit recall quality.
- Recall Latency BudgetConcept
Recall Latency Budget treats the time an agent spends re-establishing context as a line item you can measure and cap, not an invisible tax. Every session that starts cold forces the agent to re-read brand guidelines, re-derive architectural decisions, or re-ask a client's tone rules, and each of those steps burns tokens, wall-clock time, and human review hours. The budget is the acceptable ceiling on that re-establishment cost per workflow. Recognition-first systems such as Bourdon push recall toward near zero by federating memory across Claude, Codex, and Cursor, while retrieval-based layers such as Knownbase and Cogni trade a small lookup step for structured, queryable archives. For agencies running retainers, the budget compounds: a 20-minute re-brief across 40 monthly agent runs is roughly 13 hours of billable capacity. Set the ceiling before you scale agent count, because a memory layer that adds latency per hop quietly erodes the margin you automated to protect.
- Context Debt CompoundingConcept
Context debt is the accumulated cost of client knowledge that lives only in a person's head or a single chat thread: brand rules, architecture decisions, past campaign results. Like technical debt, it compounds quietly. Each new session forces the same re-explanation, and every re-prompt burns senior hours that should go to billable strategy. The framework asks agencies to treat memory as a balance sheet item, not a convenience. A recognition-first federation layer such as Bourdon lets a fact learned in one agent surface instantly in another, while a structured archive like Knownbase stores decisions by project and tag so a new hire's agent inherits the same constraints. The compounding works in reverse too: every captured decision lowers the marginal cost of the next deliverable. The risk sits on the liability side, because a memory layer that will not export cleanly converts accumulated context into a switching penalty rather than an asset.
Decision and risk
How to judge the fit, and the ways it goes wrong.
- Agent Memory Rule: Test Export Before You StandardizeEvaluation Rule
Before standardizing any client account on one memory layer, export the full store to a portable format and re-import it into a second tool, and only then make it the system of record.
- Agent Memory Rule: Federate Across Tools Before You Consolidate Into OneEvaluation Rule
Federate memory across the tools your team already runs, and treat any single-vendor memory store as a cache you can rebuild, not the system of record.
- Federated Memory Layer vs Per-Tool Project Archive: The Agency Memory DecisionDecision Framework
IF your agency runs three or more AI tools across overlapping client accounts and loses context every time work moves between them, THEN a federated memory layer that shares one knowledge store across Claude, Codex, Cursor, and similar agents pays for itself in reduced re-prompting. IF your work is concentrated in one toolchain per client and the deliverable is a single codebase or campaign asset, THEN a per-project archive scoped to that engagement is the cheaper and lower-risk path.
- Why Agent Memory Layers Rot Into Stale Client Context in Month 3Failure Pattern
- The Write-Only Memory Trap: Why Agent Knowledge Connectors Stall at RecallFailure Pattern
Delivery system
Blueprints and procedures for running it as a service.
- Cross-Tool Agent Memory Layer Build (7-12 days)Implementation Blueprint
A productized engagement that stands up one persistent, exportable memory layer so every agent on the client's stack recalls the same project decisions, brand rules, and entity relationships instead of relearning them each session.
- Memory Layer Portability Audit (Handoff)Operating Procedure
- Client Context Ingestion (Onboarding)Operating Procedure
- Cross-Agent Memory Write Discipline (Delivery)Operating Procedure
13 modules selected for RADLAB LLC
Frequently Asked Questions
Answers about pricing, setup, implementation
Bourdon is a memory federation system that lets multiple AI agents (Claude, Codex, Cursor, Copilot, Devin, Gemini, Hermes, GitLab) share a single persistent memory store. When one agent learns a fact, others instantly recognize it without latency delays. The system uses recognition-first recall to respond immediately while hydrating details in the background, and supports self-hosting or managed hosting.
Hosted Managed plan is $12 USD per seat per month and includes always-on hosting, backups, per-tenant isolation, and federation with graph memory. Enterprise plan is custom pricing and includes SSO/SAML, bring-your-own-cloud (BYOC), bring-your-own-key (BYOK), long audit-retention windows, HIPAA BAA, and a dedicated support channel. Self-hosting the memory runtime is free.
No verified white-label program. Client-facing surfaces display the RADLAB LLC brand, so you cannot present a fully branded portal to end clients. The self-hostable option allows clients to run Bourdon on their own infrastructure, but the interface itself is not customizable.
Yes. Bourdon has native adapters for both Claude and Codex, along with Cursor, Copilot, Devin, Gemini, Hermes, and GitLab. These are built-in connectors, not Zapier-only or API-only integrations, so agents can share memory immediately after configuration.
Setup time depends on infrastructure choice. Managed hosting ($12/seat/month) requires minimal configuration once the parent agency account is provisioned. Self-hosting requires client infrastructure setup and agent adapter configuration, typically 2-4 hours for a basic multi-agent fleet. Enterprise deployments with SSO and BYOC require a sales and implementation conversation.
AI development agencies building multi-agent workflows, technical teams managing internal AI agent fleets, and software companies embedding AI agents into their products. Not a fit for non-technical clients or those seeking a consumer-facing AI tool.
HIPAA BAA is available only on the Enterprise plan, which requires custom pricing and a sales conversation. The Hosted Managed plan ($12/seat/month) does not include HIPAA compliance.
If self-hosted, the client retains full control of their memory data and can continue running Bourdon on their own infrastructure at no cost. If using Managed Hosting, data retention and export policies are not detailed in available documentation; clarify with RADLAB LLC sales before signing clients onto the managed plan.