Solutions
Organic Intelligence, shaped for your team.
The four Engines compose differently for each industry and each role. Below: the industries where we go deepest, the roles each Engine speaks to first, the use cases that show up across all of them, and a triage view if you'd rather pick by the problem you're trying to solve.
By industry
Nine verticals. Nine deep-dives.
Each industry has a dedicated page with its full story: regulatory context, Engine composition, walkthroughs, platform surfaces, and where to start.
Manufacturing
Today
- ·Late projects find out late: control plans, FMEAs, and Cpk drift out of sync with the build.
- ·Supplier PPAPs arrive as PDFs and PowerPoints; quality engineers spend days verifying them.
- ·Defect chains across SAP QM, ServiceNow, and email lose context as they hop between systems.
Regulatory context
IATF 16949, VDA 6.3, AIAG core tools (PFMEA, MSA, SPC, PPAP).
Walkthroughs that show the shape
What changes
Project slip surfaces earlier. Supplier quality data lands structured. Auditors get one immutable trail.
Qualitative read. We don't quote case-study numbers we haven't measured.
Financial Services
Today
- ·Audit is sample-based; the auditor's questions land later than the violations.
- ·Segregation of duties is enforced in policy but skirted in practice (vendor master + payment run by the same actor).
- ·AP fraud finds the gaps between systems first.
Regulatory context
SOX, GLBA, NYDFS 23 NYCRR 500, PCI-DSS where applicable.
Walkthroughs that show the shape
What changes
Every transaction screened; sample-based audit replaced by hash-chained evidence; the auditor gets a re-verifiable NDJSON pack.
Qualitative read. We don't quote case-study numbers we haven't measured.
Healthcare & Life Sciences
Today
- ·PHI cannot leave the building, but the team still wants conversational analytics over patient and claims data.
- ·Access reviews come around quarterly; drift between them is invisible.
- ·Claims processing and vendor onboarding involve documents that don't fit a structured form.
Regulatory context
HIPAA, HITECH, HITRUST, state privacy (CCPA / CPRA), BAA terms on request.
Walkthroughs that show the shape
What changes
Restricted Systems route to on-prem models only; PHI redacted before the wire; HIPAA-ready posture without a separate stack.
Qualitative read. We don't quote case-study numbers we haven't measured.
Retail & CPG
Today
- ·Category and store managers wait on BI tickets that come back a week later, already stale.
- ·Promotion effectiveness is graded by gut feel; markdowns leak margin.
- ·Shrinkage patterns only surface at quarterly review.
Regulatory context
PCI-DSS where card data is in scope, plus regional privacy.
Walkthroughs that show the shape
What changes
Category drill-downs take minutes, not days. Forecasts ship with confidence bands. Loss-prevention signals surface in-line.
Qualitative read. We don't quote case-study numbers we haven't measured.
Energy & Utilities
Today
- ·Operational data lives in OT / SCADA / historian silos; IT analytics never crosses the boundary safely.
- ·Regulatory filings (FERC / NERC / EU CSRD) require evidence collection from multiple systems.
- ·Asset performance models need explainability to clear engineering review.
Regulatory context
NERC CIP, FERC, EU CSRD (ESG), regional environmental.
Walkthroughs that show the shape
What changes
Asset risk surfaces earlier. Regulatory evidence collects itself. Explainable forecasts pass engineering review.
Qualitative read. We don't quote case-study numbers we haven't measured.
Professional Services
Today
- ·Utilization and project profitability are visible only after the period closes.
- ·Proposal and SOW drafting eats partner time and reuses last engagement's content poorly.
- ·Knowledge from past engagements is hard to find when a new one starts.
Regulatory context
Client contractual confidentiality; sector-dependent.
Walkthroughs that show the shape
What changes
Variance surfaces during the period, not after. Proposals draft from prior engagements. Knowledge retrieval lands inside the workflow.
Qualitative read. We don't quote case-study numbers we haven't measured.
Transportation & Logistics
Today
- ·ETA is a phone call: buyers chase vendors and carriers by hand instead of watching a live signal.
- ·A PO can arrive in three separate shipments; no one can tell if it's 30% or 100% fulfilled.
- ·Goods receipt rarely flows back to procurement; POs stay open in reports long after the freight cleared.
Regulatory context
FMCSA/DOT, C-TPAT, CBP/ISF import filings, SOX (inventory-in-transit).
Walkthroughs that show the shape
What changes
ETA becomes a live number, not a phone call. Partial fulfillment is visible mid-flight. Goods receipt closes the loop automatically.
Qualitative read. We don't quote case-study numbers we haven't measured.
Insurance
Today
- ·AI already writes and routes claims decisions; internal audit reviews a sample long after the fact.
- ·Citizen-developer AI tools spread faster than the quarterly review cycle can track them.
- ·The same reviewer can tune a model and approve its payouts, and no one notices between cycles.
Regulatory context
NAIC AI governance model bulletin, state insurance AI circulars, SOX, GIAS-aligned audit standards.
Walkthroughs that show the shape
What changes
Every AI action carries an audit-chain entry from day one. Evidence packs assemble in minutes, not weeks. Lines of business stay isolated under one oversight view.
Qualitative read. We don't quote case-study numbers we haven't measured.
Telecommunications
Today
- ·Full-fidelity retention of network/DNS event volume is priced out before the pattern finishes forming.
- ·Low-and-slow threats sit beneath the alarms tuned for volume spikes.
- ·Blocklist and policy-zone changes happen ad hoc with no consistent before/after trail.
Regulatory context
FCC CPNI, CALEA, GDPR/ePrivacy (subscriber data), regional telecom data-retention rules.
Walkthroughs that show the shape
What changes
Windowed signal replaces uneconomical full retention. Low-and-slow threats surface before the alarm would. Every policy-zone edit leaves an immutable trail.
Qualitative read. We don't quote case-study numbers we haven't measured.
By role
A different door for every seat.
Same platform underneath. Different surface most relevant to each buyer.
CFO / Finance
Today: Numbers disagree between systems; close takes too long; auditors keep asking for more.
- ›Grounded answers that reconcile to the ledger
- ›Forecasts with confidence bands and visible assumptions
- ›Evidence collected continuously instead of at month-end
Week one: Stops re-explaining the same variance to the board.
COO / Operations
Today: Exceptions surface in dashboards instead of in workflow; approvals get stuck in inboxes.
- ›Exception routing in the same surface as the work
- ›SLA-bound approvals with decision context attached
- ›24/7 background pipelines for the repetitive parts
Week one: The Inbox replaces the Slack DM that asked for approval.
CIO / CTO
Today: Every AI vendor wants to be its own platform, its own auth, its own audit.
- ›Customer-installable: SaaS, VM, Kubernetes, air-gapped
- ›Your IdP, your KMS, your LLM keys
- ›Clean SBOM, signed artifacts, no analytics on authenticated pages
Week one: Procurement reads the SOC 2 mapping and the BAA terms in the same week.
CISO / Risk
Today: AI initiatives keep landing outside the governance perimeter.
- ›AI Trust Layer (filters, injection detection, model allowlist, classification cap)
- ›Composite 0-100 risk score on every Reaction
- ›Hash-chained audit; evidence pack the auditor can re-verify offline
Week one: Sees the first 'this AI call would have crossed our restricted ceiling' denial in the Trust Event log.
Controller / Compliance
Today: Sample-based controls testing scales linearly with the team.
- ›Every transaction screened against every policy
- ›SoD pair detection and dual-approval enforcement
- ›Findings escalate into tracked, owned Action Items
Week one: Replaces the quarterly SoD spreadsheet with a continuous feed.
Head of Analytics
Today: Self-service BI either lies fluently or doesn't ship.
- ›NL→SQL grounded in your schema with cited rows
- ›Pre-validated follow-ups skip nl-to-sql on the second click
- ›Trust Layer keeps PII out of prompts before it leaves
Week one: First answer the team trusts enough to forward without rewording.
Use cases
Patterns that show up everywhere.
Industry-agnostic shapes. Each maps to an Engine combo and a walkthrough that demonstrates it on real surfaces.
Email-PDF to ERP automation
Inbound vendor invoices and quality submissions arrive as email + PDFs. The Mailbox connector triggers an intake Chain that extracts, validates, matches, routes for HITL, and posts to SAP or NetSuite under one immutable audit row.
→ Defect handling chain (same pattern as AP)Typical pace: First end-to-end Reaction in days; broader rollout in weeks.
Inbound freight visibility
ERP purchase orders, supplier ship notices, and carrier tracking events join into one PO-level record with a live ETA and a confidence score, read in place rather than copied into a warehouse first. When a shipment stalls (a border hold, a missed handoff), a Chain gathers the detail and asks a planner to pick the response in the Inbox. Suppliers post ship notices through a scoped self-service portal, and proof of delivery posts the goods receipt back to the ERP, with a human confirming any quantity variance.
→ Inbound freight: border hold to goods receiptTypical pace: First live ETA dashboard within days of connecting the ERP and one carrier feed.
Natural-language analytics
Finance, RevOps, and operations teams ask questions in plain English and get cited, charted answers. Follow-ups carry pre-validated SQL so the second question skips the LLM round-trip.
→ Question → chart → follow-up → drillTypical pace: First trusted answer within days of schema-prompt tuning.
Continuous controls monitoring
Every transaction across your warehouse and ERPs evaluated against every policy, in real time. SoD, threshold, repeat-pattern, and reference-only policies all editable inline with before→after audit diffs.
→ Failed-login + SoD correlationTypical pace: First findings within hours of connecting a System.
AI-assisted approvals
Risk-scored approvals with the policy match and the model trace attached. Routed to the right approver on the right channel (Inbox, Teams, email). SLA-bound; auto-escalates on timeout.
→ High-risk pauses itself · low-risk runsTypical pace: First HITL gate live in the Inbox the same day the auto-HITL threshold is set.
Executive briefings
Weekly or on-demand briefs that combine Insights answers, Governance findings, and Advisory recommendations. Delivered on your schedule, with provenance for every line.
→ Conversational pattern that powers the briefTypical pace: First weekly brief landing within two weeks of the first Skill.
AI governance for an existing stack
You already have an agent framework (Agent Core, Step Functions, Bedrock, n8n). Quadrazene becomes the governance plane underneath: Trust Layer guards every LLM call, Risk scores every run, Records keeps the trail.
→ Quadrazene called as a toolTypical pace: First governed call from your orchestrator the same day the API key is issued.
Managed platform operations
A large on-prem data platform (hundreds of nodes, several compute engines, shared storage, an incumbent monitoring tool being retired) generates more signal than a support team can triage by hand. Quadrazene turns the collected health, job, and capacity telemetry into Radar dashboards and drills from a slow workload down to the task and log behind it. It correlates the noise, matches the incident to a cited runbook, opens and enriches the ITSM ticket, and routes consequential changes through HITL in Teams. Models run inside the perimeter, and every action lands as one audit row.
→ Slow job to approved fix before the morning reportsTypical pace: First dashboards and correlated alerts within weeks of the telemetry feed landing.
High-volume event-stream intelligence
Some telemetry streams run at a volume where keeping everything is priced out before a pattern finishes forming. Quadrazene captures windowed signals from the stream instead: a context pass suggests which signals matter, an operator approves them, and capture runs from there. Low-and-slow anomalies surface beneath alarms tuned for volume spikes, Advisory proposes the response, and block or policy changes go through HITL with a before/after trail.
→ Keep the signal, not the streamTypical pace: First approved signal catalog within days of connecting the stream.
Post-acquisition data unification
A merger leaves customer, product, and vendor masters duplicated across CRM, PIM, and ERP systems. Quadrazene's entity-resolution pipeline fuzzy-matches, clusters, and proposes merges with an LLM-adjudicated rationale — a human confirms the ones that matter, and the golden record keeps a full survivorship trail.
→ Evidence-pack pattern (reuses for merge-decision audit trail)Typical pace: First reconciled entity cluster within the first data connection.
Pick your starting point
A triage view, by the sentence you'd actually say.
If one of these problems sounds like yours, follow the line. Engine to start with, walkthrough that shows it.
“Our SOX testing keeps finding the same SoD violations after the fact.”
“Variance and close commentary takes the team a week.”
“PPAPs, 8Ds, and QM notifications are eating quality engineers' time.”
“We have an AI stack already; we just need it governed.”
“The forecast doesn't reflect what we're actually seeing on the ground.”
“We can't put patient or financial data in a hosted LLM.”
None of these fit? The platform is general-purpose. Tell us the sentence you would actually say and we'll point at the relevant Engine and walkthrough together.
What a deployment looks like
From first conversation to running in production.
Four phases. Each is its own engagement; you can stop after any of them. The full mechanics live on the Approach page; this is the summary.
Discovery
A working session. Bring a question you wish your analytics already answered.
DaysPilot
A scoped scenario, your data, your IdP. One Engine deeply, one walkthrough live, evidence we can both review.
WeeksProduction
Roll out the Engine across the team, bond a second Engine, wire your SIEM and your KMS.
Weeks-to-monthsPartnership
Ongoing tuning, new walkthroughs, more Engines bonded. We stay in the loop or step back, your call.
OngoingDon’t see your industry, role, or use case?
The platform is general-purpose. Tell us the sentence you would actually say and we’ll point at the relevant Engine and walkthrough together.