When the wrong answer costs more than no answer at all.
Andromeda is the digital knowledge twin for critical cost surfaces — the equipment, processes, and decisions your business can't afford to get wrong. We turn scattered manuals, service records, and institutional knowledge into answers your teams can act on and your organization can stand behind.
Thought
Parsing symptom: thermal stall under sustained PTO load
Viewed
JD-5075E §4.2TSB-TR-1187Field Rpt '23Cooling v3+3 moreAnalyzing
Cross-referencing overheating patterns with fuel delivery logs
Root Cause
Cooling efficiency drop under load > 85% throttle
12 Sources
JD-5075E-SVC-MANUALTSB-TR-1187Warranty Claims Q4Field Data – Midwest
“Why does my combine stall after 20 minutes under load?”
2:14 PM
Diagnosis
The tractor is stalling due to thermal fuel vapor lock caused by restricted airflow in the radiator assembly. Under sustained PTO load, engine temperature rises beyond optimal range, triggering fuel system instability and ECU protective shutdown.
Contributing Factors
- •Debris accumulation in radiator fins
- •Partial fan clutch failure
- •High ambient temperature (>95°F)
- •Fuel line routing near exhaust manifold
Recommended Steps
- 1.Inspect and clean radiator core and shroud.
- 2.Verify fan clutch engagement at operating temperature.
- 3.Confirm fuel line insulation integrity.
- 4.Perform ECU thermal threshold calibration check.
Confidence
Sources (12)
Reasoning
Overheat pattern matched across 3 independent sources
Born from national security. Built for industry.
Andromeda's architecture was forged in environments where accountability isn't a feature — it's a mandate. We brought that standard to the enterprises that need it most.
Andromeda
What changes when your knowledge actually works
Answers that reason, not just retrieve
Most AI tools find the document chunk that matches your question and hope the language model gets it right. Andromeda reasons across your entire knowledge base — connecting assets to configurations, configurations to procedures, procedures to incident history — and delivers a structured diagnosis with every source traced.
Graph-grounded architecture means answers reflect verified relationships across your documentation, not statistical best-guesses from isolated text fragments.
First-time fix by default
Every answer is tailored to the specific asset, configuration, and service history in front of the technician. No generic procedures. No "call the person who knows." Andromeda delivers the right diagnosis, right steps, and right parts — because it understands how your equipment, documentation, and history relate to each other.
Reduces mean time to resolution by eliminating the search-escalate-search cycle that consumes hours per incident across maintenance, service, and compliance workflows.
Built for the signatures that matter
Your compliance team. Your safety officers. Your legal counsel. Your regulators. These are the people who need to say "yes" before AI touches critical operations — and they won't sign off on a black box. Every Andromeda response shows its reasoning chain: which sources informed it, what confidence level applies, what gaps exist.
Full provenance and audit trail — not just "here's the PDF it came from," but a reconstructable path from question to answer to source to decision.
Knowledge that doesn't walk out the door
Your best technician's 30 years of pattern recognition. The engineer who knows which failure mode the manual doesn't cover. The tribal knowledge that lives in hallway conversations and retirement parties. Andromeda captures the relationships between assets, failure modes, procedures, and institutional history — making organizational knowledge structural rather than personal.
Relationships no single person could hold in their head — persisted as structure across siloed systems and queryable by anyone in the organization.
If it's a critical cost surface, it's our kind of problem.
Every organization has critical cost surfaces — the equipment, processes, or decisions where the financial, safety, or regulatory cost of a wrong answer dwarfs the cost of getting it right.
For a manufacturer, it's the serviceability and uptime of the machines their customers' livelihoods depend on. For an aviation maintenance team, it's the airworthiness of the aircraft under their care. For a financial institution, it's the compliance decision that could trigger regulatory action.
These are the places where “good enough” AI is genuinely dangerous — and where Andromeda goes deepest.
Manufacturing & Heavy Equipment
Serviceability, uptime, field operations
Aviation & Aerospace
Airworthiness, maintenance compliance
Defense & Mission
Decision intelligence, operational readiness
Regulated Industries
Financial services, healthcare, insurance
Who it's for
Built for teams where the stakes are real
Maintenance & Reliability Leaders
Your technicians shouldn't need 20 years of experience to troubleshoot like someone with 20 years of experience. Andromeda puts expert-grade diagnostic support in every technician's hands — grounded in approved procedures, asset history, and institutional knowledge, not generic AI guesswork.
Key outcomes
- Cut unplanned downtime
- Enforce consistent playbooks across plants, shifts, regions
- Stop losing expertise to retirement and transfers
Service & Field Operations Leaders
Your field teams shouldn't arrive on-site blind and spend the first hour searching. Andromeda delivers job-ready context before they open the panel: asset configuration, prior visit history, parts used, known edge cases, and relevant bulletins — all connected, all cited.
Key outcomes
- Increase first-time fix rates
- Reduce return visits
- Reclaim hours spent searching portals and binders
Engineering, Safety & Compliance Leaders
Close the loop from field to design to regulation. Incidents, near-misses, and recurring failure patterns get captured as structured knowledge — not buried in email threads or spreadsheets. Ensure frontline teams always see the latest approved guidance, with a traceable history of what changed and why.
Key outcomes
- Surface recurring failure patterns
- Ensure current approved guidance reaches frontline
- Give compliance a defensible audit trail
Beyond the current wedge
Today, Andromeda goes deepest in equipment-intensive operations — manufacturers, aerospace, industrial field service. But the architecture was built for any environment where accountability isn't optional. If your organization has complex documentation, distributed knowledge, and real consequences for wrong answers — the same platform applies.
How it works
AI that understands your operation, not just your documents.
Most AI tools treat your documentation as a pile of text to search through. Andromeda treats it as a domain to understand — extracting the entities, relationships, and logic that make your operation work, then reasoning across them to deliver answers your teams can verify and your organization can defend.
Step 1
Connect to your knowledge — wherever it lives
Plug in your technical manuals, service records, work orders, specifications, bulletins, and operational data. Andromeda connects to your systems as they are — no migration, no duplication, no disruption to existing workflows.
Your data stays where it is. Scheduled and incremental sync keeps your knowledge current.
Step 2 — the architectural difference
Build a knowledge graph — not a search index
This is where Andromeda diverges from every other AI tool on the market.
Most systems chunk your documents into text fragments and store them as vectors — a search index that matches keywords and proximity. Andromeda does something fundamentally different. It reads your documentation the way a subject matter expert would: extracting the assets, components, procedures, failure modes, specifications, and regulatory references — then mapping the relationships between them.
From Similarity Search to Structured Diagnosis
Text Chunking
Fragmented context — meaning is lost
Vector Embedding
Cosine similarity scoring
“Best Match”
Probabilistic — no explicit relationships
“Why did Unit 14 fail inspection?”
Based on the available documentation, Unit 14 may have failed inspection due to issues related to hydraulic pressure readings. The inspection report mentions several potential factors that could have contributed to the failure.
No structured diagnosis. No reasoning trace. No provenance chain.
Entity Extraction
Structured entity modeling
Knowledge Graph
Verified relational links
Constraint-aware, deterministic
Step 3
Ask questions — get answers that show their work
Your teams ask questions in plain language. The AI reasons across the knowledge graph — traversing verified relationships between assets, configurations, procedures, and history — and delivers a structured response. Not “here's a paragraph that mentions your keywords.” A diagnosis with steps, parts, cited sources, confidence levels, and the full reasoning chain visible.
- Every answer traces back to source.
- Not "here's the PDF it came from" — a reconstructable path from question to answer to source to decision.
- Every reasoning path is visible.
- Your compliance team can audit it. Your safety team can verify it. Your technicians can trust it.
- Confidence levels are explicit.
- Andromeda tells you what it knows, what it's uncertain about, and where gaps exist — rather than presenting everything with false confidence.
“Why did Tractor Unit 14 fail inspection after PM-3021?”
Traversing Verified Relationships
Evidence (9 Sources)
Maintenance Log – 03/14
Matched via asset relationship
Valve Pressure Spec Sheet
Matched via part association
Incident Case #4831
Historical pattern match
Service Bulletin SB-204-11
Procedure cross-reference
Structured Diagnosis
Hydraulic pressure valve exceeded tolerance due to improper torque specification during PM-3021, causing pressure instability and inspection failure.
Required Actions
- 1.Replace valve assembly (PN-88X)
- 2.Recalibrate pressure settings
- 3.Re-run inspection procedure
Full Reasoning Chain
Confidence: 82%
↑ Multi-source agreement
⚠ Limited temp data
Sources (9 Verified)
Audit
Ready
Step 4
Deploy where your data lives — on your terms
The platform is built on open, modular infrastructure — not locked to any single database, vector store, or search engine. If your environment already runs approved components, Andromeda integrates with them. No vendor lock-in, no forced migration, no architecture tax.
Multi-tenant cloud. Dedicated cloud. On-premises. Air-gapped at the tactical edge. Andromeda deploys into your security posture — inheriting your permissions, plugging into your identity infrastructure, and meeting your compliance requirements.
If your compliance requirements dictate specific vendors, we adapt. Swappable components at every infrastructure layer mean you're never locked into our choices.
For technical evaluators — interactive 5-layer model, component details, and infrastructure specifics.
Multi-tenant cloud
Fastest deployment, lowest TCO
Dedicated cloud
Enhanced isolation, custom SLAs
On-premises
Complete data sovereignty
Air-gapped / Edge
Tactical edge, DDIL environments
Start with your most critical cost surface. Prove the impact.
Pick the product line, asset family, or documentation set where wrong answers cost the most. Deploy Andromeda against that single surface. Measure the reduction in search time, escalations, and repeat incidents. Then expand.
Accountable Intelligence. Every answer backed. Every source traced.