For Enterprise Leaders · Fortune 500 & regulated industries

Ship AI your whole team can trust: production hardened, audit ready accuracy.

Knowledge graph systems on Neo4j that ground every AI answer in your data. Production hardened GraphRAG with measurable hallucination reduction in controlled enterprise testing. Built by a senior team, measured in production: deployed inside your own cloud.

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No obligation. In 30 minutes we’ll show you 3 compliance or architecture risks blocking your next AI release.

15+ enterprise clients · 95% extend engagement · Neo4j Solution Partner

Deploys in your VPCZero data egressSOC 2 aligned deliverySSO / RBAC / audit logsYou own 100% of the IP
Compliance ready architecture:PCI DSSHIPAAGDPRSOC 2 Type IIISO 27001FedRAMP
Outcomes · measured in productionclient data · verified against baselines
BASELINE
80%
Fewer hallucinations vs. baseline
CITED
99.2%
Answers grounded with citations
SIGN OFF
90 days
Audit to production sign off
IN PROD
50+
Enterprise clients in production

Sound familiar?

These are the problems enterprise leaders bring us most often. If any of them sting, the briefing will pay for itself.

01

Data is your biggest blocker, not your team

Your AI prototypes work in the lab but hallucinate on real, fragmented enterprise data. Compliance teams are skeptical: and they’re right to be.

02

Hiring isn’t the answer

You can’t hire a full graph engineering team overnight, and your existing engineers don’t have the specialized knowledge. Six months of recruiting buys you a bench, not a system.

03

The board is losing patience

AI initiatives are critical to your market position: and they’ve been stuck in the R&D phase for quarters while competitors ship.

Conservative math: every quarter of delay costs $650K+ in stalled initiative burn, manual verification tax, and risk exposure , more than the entire system that fixes it.

See the system

The artifacts your architects will actually review

Not promises: the architecture your security team can verify and the console your analysts will use. Forward this to your review board.

architecture: reviewed by your security team
zero data egress
YOUR VPC · YOUR CLOUDYOUR SYSTEMSSnowflakeSAPSalesforceSharePointNeo4j · governedKnowledge graphGraphRAG engineretrieval by traversalCited answerprovenance on every replyCONTROLSSSO / RBAC · human in the loop · immutable audit log · eval gatesUSERS ENTER VIA SSO: DATA NEVER LEAVES
1

Ingest

in your VPC

2

Govern

on Neo4j

3

Cite

every answer

grounded answer console: what your analysts see
live · production

Query

What is our total exposure to Meridian Holdings across all desks?

Total exposure is $14.2M across 3 desks: $8.1M rates [1], $4.4M credit [2], $1.7M FX [3]. Collateral held covers 71% [4].

[1]trade_ledger.rates · desk RT-02 · as of 09:00 UTC

[2]credit_book.q3 · counterparty id CPTY-4471

[3]fx_positions.eod · netted

[4]collateral_mgmt.snapshot · ISDA CSA

✓ grounded · 99.2%evidence path: Party → Trade → Desklogged · audit id #88412

Enterprise · Audit ready

Zero audit findings. Every answer cited.

Not a vendor's install base: ours. Every number below is a claim we make about our own delivery, checkable against the pilot we run for you.

15+

Enterprise clients

95%

Extend engagement

0

Audit findings, 3 quarterly reviews

100%

Response citations in production

SOC 2HIPAAGDPRPCI DSS

Deployed in your VPC

On your cloud, your controls: zero data egress by default.

Citation on every answer

Every response traces back to a source your compliance team can click.

Hallucination reduction guaranteed

The target is agreed in writing before week one. Miss it and the pilot is free.

Neo4j Solution Partner

Graph infrastructure built on Neo4j. Delivery, guarantees and support are ours.

Graph infrastructure is built on Neo4j; we are a Neo4j Solution Partner, not Neo4j Inc. The delivery numbers above are ours.

Category · Market direction

Is the graph database market actually growing?

The Answer

Yes. Five independent market-research firms and Gartner all project strong growth through 2030, though none agree on the exact figure: estimates for 2030/31 range from roughly $8B to $14B, at a 22 to 30% compound annual growth rate.

We're showing the range instead of the single most impressive number, because that's the version a buyer can actually verify.

$0.5B to $4B

Today (2024 to 2026)

22% to 30% CAGR

$8B to $14B

By 2030 to 2031 (est.)

Estimate range, not a single-source figure. Sources: ResearchAndMarkets, Technavio, MarkNtel Advisors, IndustryARC, Mordor Intelligence, and Gartner's Market Guide for Graph Database Management Systems. Figures vary by firm and methodology; treat as directional, not precise.

Enterprise · Why graph

The deeper the relationship, the wider the gap.

As query depth increases, relational joins compound and slow down. Graph traversal cost stays close to flat, because it follows relationships instead of re-joining tables.

~11× the height by 6 hops
1 hop2 hops3 hops4 hops5 hops6 hops
Relational joinsGraph traversal

12+ joins, one query

Every hop re-executes the join.

A few hops, one traversal

Same cost, no matter the depth.

Illustrative, not a measured benchmark on your data. Reflects the widely documented shape of graph vs relational performance as relationship depth increases; run your own workload to see your numbers.

The Enterprise Grounded AI System

Everything required to take AI from “blocked by compliance” to “signed off and in production”: delivered as one system, not a slide deck.

Enterprise ontology & knowledge graph architecture

Your entities, relationships, and business rules modeled into one governed graph: the single source of truth your AI reasons over.

$120K value

Production GraphRAG pipeline + evaluation harness

Retrieval that traverses the graph instead of guessing from embeddings, with an eval suite that measures hallucination rate against your baseline: continuously.

$180K value

Compliance & citation layer

Per answer source citations, reasoning traces, human in the loop approvals, and immutable audit logs. The artifact your risk committee actually signs off.

$90K value

In VPC security deployment

Everything deployed inside your cloud with SSO/RBAC integration and zero data egress. Verified at the network level by your own team.

$60K value

Team enablement & full IP handover

Documentation, runbooks, and pairing sessions so your engineers own and extend the system. No lock in, no black boxes.

$45K value

Confidential 30 minute architecture briefing + written recommendation

Three documented savings opportunities of $50K+ each, mapped to your architecture. Yours to keep whether or not we ever work together.

No cost: today

Combined standalone value: $495K+ · Your first step costs $0 and 30 minutes

The pilot guarantee

Hit the agreed hallucination reduction target on your data: or the pilot is free.

Before the pilot starts, your team and ours agree the evaluation baseline and the reduction target in writing. We measure on your data with your people watching. If we miss the performance targets, the pilot is free (no exceptions) and you keep every finding.

Built for the world’s most regulated industries

Your data is your competitive advantage. We treat it that way: compliance is architected from day one, not bolted on.

Private AI deployment

Your data stays on your infrastructure. No training on your proprietary data. Ever.

SOC 2 Type II aligned delivery

Audited grade processes and controls across engineering and operations.

HIPAA ready architecture

Designed to handle protected health information (PHI) with full audit trails.

GDPR compliant data handling

Right to forget, data portability, and strict access controls built in.

Audit ready explainability

Every AI answer traceable to source documents with full provenance.

Data sovereignty

Deploy regionally or in your specific cloud: AWS, Azure, or GCP.

The bottom line: you get the competitive advantage of AI without compromising on security, privacy, or compliance.

Promise 1 · Grounded truth

Every answer cited: or it doesn’t ship.

Compliance grade AI, grounded on your knowledge graph. Each response carries a traceable evidence path back to source systems: the artifact your auditors actually accept.

Promise 2 · Compliance velocity

Your risk committee approves. In weeks, not quarters.

Citations, audit logs, and human in the loop controls are built in from day one: so review boards say yes to production instead of killing another pilot.

Why Fortune 500 leaders choose us

We are Neo4j experts

We don't just implement knowledge graphs: we architect them for scale, performance, and accuracy.

We ship, we don't consult

You get a working system, not a PowerPoint. Average time to production: 6 weeks.

We handle compliance

SOC 2, HIPAA, GDPR, and private AI deployments are standard in our delivery.

You own everything

Built in your repo, on your infrastructure. No vendor lock in. Ever.

1Client request + advisory

Not “what do you want?” Here’s what works.

We don’t open with a 40 page intake form. Your request lands; a senior architect and compliance lead reply with a concrete shape, drawn from every comparable system we’ve taken through a risk committee. Recommendations, not interrogation.

SC

Sarah Chen · CTO, Meridian Bank · client

“Our AI copilot is blocked in model risk review. Legal won’t approve anything it can’t verify.”

briefing · 30 min  →  scoped plan · week 1Epic: Grounded AI

Advisory · Agentic Giants architect + compliance lead

Drawn from Fortune 500 financial services engagements

For a business like yours, we recommend:

  • GRAPH

    GraphRAG layer on your existing data fabric no migration: the graph connects your 14 systems where they are.

  • EVAL

    Measurable hallucination reduction eval baseline agreed with your model risk team, tracked in production.

  • SEC

    Private AI deployment SOC 2 / HIPAA-ready architecture: no data ever leaves your infrastructure.

  • LOG

    Audit logging for every interaction provenance on every answer, regulator ready export.

Drawn from our knowledge base of past engagements: the same graph technology we sell.

Briefing to sign off in 90 days

Staged commitment: you decide again at every milestone, with evidence in hand.

  1. Day 0

    Confidential briefing call

    30 minutes with a senior architect. We map where your AI answers come from and where they'll fail review.

  2. Week 1

    Findings report

    Three documented savings of $50K+ each and a pilot scope with an agreed evaluation baseline.

  3. Weeks 2 to 6

    Guaranteed pilot on your data

    Graph + GraphRAG on a real use case, measured against the baseline. Miss the target, pilot is free.

  4. Weeks 7 to 12

    Production & sign off

    Hardened deployment in your VPC, compliance documentation, team handover. Regulators see citations, not vibes.

“Our compliance team went from blocking every AI feature to approving them: because now every answer has a source.”

Head of Data · Fintech (RYVYL) · Measurable hallucination reduction in production

Trusted by teams at

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One honest constraint: every build is led by senior engineers, the same people on this page’s numbers, so we take on a limited number of enterprise engagements per quarter. The briefing costs nothing and commits you to nothing, but pilot slots are scheduled in the order briefings complete.

Enterprise questions, answered

We offer private AI deployment: your data stays on your infrastructure and we never train on your proprietary data. The architecture supports SOC 2, HIPAA, and GDPR requirements, with SSO/RBAC integration and audit logging for every AI interaction.

Relevant client results

View all case studies →

Ready to ship AI your whole team can trust?

One 45 minute confidential briefing with our senior architects. We’ll review your AI roadmap, data infrastructure, and compliance requirements: and deliver a written architecture recommendation. It’s yours either way.

✓ No obligation  ·  ✓ The recommendation is yours either way  ·  ✓ Pilot backed by the performance guarantee