Production Graphiti knowledge graph with FalkorDB backend
Pilot · 4–6 Weeks
Knowledge Graph & LLM Pilot
Production-grade temporal knowledge graphs and RAG pipelines built on top of your existing CRM and ERP — without ripping out what you already have. Graphiti + FalkorDB + LightRAG + Ollama, deployed in 4 to 6 weeks.
4–6 weeks $15k–$40k
Limited slots · First-cohort pricing · Your competitors are already automating
Graphiti shipped in late 2024. FalkorDB is a Redis-backed graph database that still feels like a secret weapon. LightRAG is a 2024 research project that's suddenly usable in production. In April 2026, fewer than 1,000 developers worldwide have any of these running in production.
9o4t Inc does. Today. We run Graphiti + FalkorDB as our primary memory layer, mirrored to Railway Postgres, with Ollama (llama3.2, mistral) serving local LLM inference and OpenAI handling structured-output tasks. It's not a pitch deck — it's the stack you'd be hiring us to build for you.
We run 4-to-6 week pilots that answer a specific business question: "Can a knowledge graph over our last seven years of Salesforce notes surface the pattern we've been missing?" At the end of the engagement you get a working system, a decision framework for productionizing it, and candid recommendations on what not to build.
The first-mover window on this is closing. The premium 9o4t can charge for production knowledge-graph work evaporates the moment it becomes commodity — and so does the moat your business gets from being early. Pilot now, while it's still a competitive edge instead of table stakes.
Deliverables
What You Get
- RAG pipeline integrating your CRM/ERP data with LLM responses
- Hybrid local-plus-cloud LLM deployment (Ollama + OpenAI)
- Ingestion pipelines from Salesforce, NetSuite, HubSpot, email, docs, or files
- Domain-specific entity and relationship extraction tuned to your data
- Executive demo + technical handoff documentation
- Build-vs-buy recommendations for the productionization phase
- Honest assessment of what the graph can't tell you yet
Why 9o4t
We Run This Stack Today
Graphiti + FalkorDB (primary), Railway Postgres (mirror), LightRAG, and local Ollama models are all live on our own infrastructure. You are not paying for us to learn on your data.
First-Mover Pricing Window
Kubernetes consultants in 2015 charged $300–$500/hour because almost no one had production K8s experience. Snowflake consultants hit similar windows. Knowledge graphs are in that window right now — and the first-mover premium goes away inside 18 months.
Enterprise CRM Bridge
Most AI consultants can build RAG over a pile of PDFs. We can build RAG over Salesforce notes, NetSuite transactions, and HubSpot email threads, with the domain context of someone who's shipped SuiteScript for a decade. That bridge is rare.
Privacy-Conscious Deployment
Graphiti extracts entities via OpenAI (structured JSON mode). Embeddings run locally via Ollama's nomic-embed-text. For clients who can't send data to OpenAI, we can swap extraction to local Mistral and keep the entire stack on-prem.
Fit Check
Ideal For
- Enterprises with years of unstructured data in Salesforce or NetSuite they can't search effectively
- Law firms, consultancies, and agencies wanting pattern recognition across case/project histories
- Mid-market companies exploring AI but afraid of 'consultant who read the docs last week'
- Tech-forward organizations wanting a privacy-first local LLM deployment (Ollama-based)
- CRM and ERP vendors building knowledge-graph add-ons or plugins
- Founders who need a defensible AI moat, not a ChatGPT wrapper
FAQ
What is Graphiti and why does it matter?
Graphiti is an open-source temporal knowledge-graph library released in late 2024, optimized for LLM agents. It tracks how facts and relationships change over time — which is critical for enterprise use cases where 'who was the account owner in Q2' has a different answer than 'who is the account owner now.' Traditional RAG loses that context.
Why FalkorDB instead of Neo4j?
FalkorDB is Redis-based, faster for the query patterns knowledge graphs hit (short, graph-local traversals), and dramatically cheaper to operate at mid-market scale. Neo4j remains excellent for analytics-heavy graph workloads — FalkorDB wins for agentic memory.
Do we have to give our data to OpenAI?
No. The default Graphiti stack uses OpenAI only for entity extraction (requires structured JSON output), but we can swap in local Mistral for fully on-prem deployments. Embeddings already run locally via Ollama (nomic-embed-text). Many clients in regulated industries choose the all-local path.
What does a 4–6 week pilot actually deliver?
A working system pointed at a real slice of your data (typically 6–12 months of CRM notes or documents), answering a specific business question you defined at kickoff. Plus a technical handoff and a recommendation: productionize, extend, or kill. We bias toward honest assessments over upsells.
How does this compare to just using ChatGPT or Claude?
ChatGPT and Claude are excellent for one-shot reasoning, but they don't remember your account history across conversations and can't traverse your CRM graph. A knowledge graph gives the LLM a durable, queryable memory of your business — closer to how a senior employee carries institutional context.
What happens after the pilot?
You own the code and the system. Options: take it in-house, hire 9o4t to productionize it (roadmap, hardening, SLAs — typical $50k–$150k annual retainer), or decide the use case doesn't justify the investment and walk away. We'll tell you which path is right.
Don't Wait
Every Week You Wait Is Money Left on the Table.
Your competitors are already automating. David Cullum scaled a telecom brokerage from $50M to $150M — and he still ships code. Lock in first-cohort pricing on the $999 AI Assessment before the slots are gone.
Limited slots
Skip the line.
Tell David what's eating your week. You'll hear back within one business day — usually faster.