Decyra Autonomous Architecture • 2026 Core

THE DECYRA AGENTIC AI SUITE

Six specialized autonomous agents and security protocols powering your enterprise data fabric. Moving enterprise intelligence beyond passive prompt-response chatbots into self-healing, root-cause investigation, and zero-egress data privacy.

Zero Data Egress

Confidential customer records and financial ledgers never touch Decyra servers. All computation happens in temporary client RAM or in-place on your cloud storage.

Autonomous Self-Healing

Eliminates the #1 flaw of AI analytics: broken SQL queries. The reflection loop catches database engine errors, corrects syntax in 25ms, and delivers perfect answers.

Autonomous Anomaly Watchdog

Sentinel proactively scans live metrics at 7:30 AM before executive standups, detects trend breaks, and emails leadership root-cause explanations without human prompts.

Architecture Deep-Dive

The 6 Autonomous Agents & Protocols

Detailed breakdown of operational logic, execution traces, enterprise business value, and technical defensibility.

01

Decyra Vault™

Zero-Egress In-Memory Privacy Architecture

Security & Confidentiality ProtocolLIVE

How It Operates in Decyra

Unlike traditional cloud analytics platforms that ingest, replicate, and persist your database rows on external servers, Decyra Vault executes all schema discovery, SQL planning, and vector querying strictly inside temporary client-side browser RAM or in-place directly on your cloud lakehouse via HTTP range requests. When the browser tab or query session finishes, the memory is wiped clean. Zero customer records ever touch Decyra disks.

Execution Protocol Steps
  • 1Client browser initiates encrypted TLS 1.3 session directly with data source.
  • 2Only structural table metadata (column names, data types, row counts) is inspected.
  • 3ANSI SQL query runs in client-side WebAssembly RAM or directly in-place in Cloud Storage.
  • 4Results are rendered directly to memory; zero raw data is persisted or logged.
Business Impact

Overcomes strict enterprise procurement barriers. Data protection officers, CISOs, and legal teams approve Decyra without fear of data leakage.

Defensible Moat

Instant compliance certification (SOC2 Type II, HIPAA, GDPR-ready) with zero server-side storage infrastructure liability.

Agent Execution Stream
Groq LPU Runtime
DECYRA_VAULT::SESSION_INIT -> Memory Buffer Allocated: 64MB [Isolated RAM]
DECYRA_VAULT::EGRESS_CHECK -> Remote storage: BLOCKED | Raw disk write: DISABLED
DECYRA_VAULT::STATUS -> 100% Client-Side In-Memory Execution Confirmed ✓
Autonomous State: ActiveStatus 200 OK
02

Auto-Healing SQL

Real-Time Query Error Correction & Self-Reflection

Reliability & Execution EngineIN PROGRESS

How It Operates in Decyra

Enterprise databases are messy. Columns get renamed (e.g. 'mrr_usd' vs 'monthly_recurring_revenue'), date formats differ, and SQL dialects clash between PostgreSQL, Snowflake, and BigQuery. When an execution engine throws a syntax or column error, the Auto-Healing SQL agent catches the error trace, feeds the engine diagnostic into a reflection loop, corrects the query structure, and re-executes in under 30 milliseconds before returning the answer to the user.

Execution Protocol Steps
  • 1Planner Agent generates candidate ANSI SQL from natural language prompt.
  • 2Engine dry-run executes query; traps dialect or syntax mismatch (e.g. column missing).
  • 3Reflection Agent parses stack trace, cross-references schema dictionary, and resolves alias.
  • 4Corrected SQL executes successfully with complete audit trail preserved.
Business Impact

Eliminates frustrating 'Query Failed' red error banners. Non-technical operators and executives get reliable answers on the first try without relying on data engineers.

Defensible Moat

Boosts prompt-to-answer completion rate from the industry average of 74% to >98%, cementing high net-revenue retention.

Agent Execution Stream
Groq LPU Runtime
ERROR 42703: column "client_name" does not exist in table "accounts"
AUTO_HEAL::AGENT_TRIGGERED -> Reflection loop parsing schema graph...
AUTO_HEAL::MAPPING_RESOLVED -> Substitute column: "account_title"
AUTO_HEAL::RE_EXECUTE -> Success in 24ms. 1,420 rows returned ✓
Autonomous State: ActiveStatus 200 OK
03

Sentinel™

24/7 Autonomous Revenue Watchdog

Autonomous Operations & AlertingIN PROGRESS

How It Operates in Decyra

Sentinel doesn't wait for humans to ask questions. Operating on scheduled cron intervals or real-time event webhooks, Sentinel calculates 7-day and 30-day statistical baselines, detects metric anomalies (e.g. >2.5 standard deviations in churn or signups), runs diagnostic sub-queries to isolate the cause, and dispatches proactive executive briefs to leadership via Email and Slack at 7:30 AM before daily standups.

Execution Protocol Steps
  • 1Scheduled trigger initiates automated metrics scan against live connected sources.
  • 2Statistical engine compares rolling trendlines vs. expected seasonality.
  • 3Anomaly Detection: Flags significant shifts in ARR, renewal rate, or pipeline velocity.
  • 4Autonomous Synthesis: Drafts concise executive email with root-cause context and recommendations.
Business Impact

Transforms executive leadership from reactive fire-fighting to proactive intervention. Catches a $100K churn risk days before the quarter ends.

Defensible Moat

Creates continuous daily active engagement. Executives receive direct enterprise value in their inbox every morning even when they don't log in.

Agent Execution Stream
Groq LPU Runtime
SENTINEL::SCHEDULED_RUN -> 07:30:00 UTC [Automated Wakeup]
SENTINEL::METRIC_ANOMALY -> North America Enterprise Renewals: -28.4% WoW
SENTINEL::INVESTIGATION -> 2 accounts stalled in legal redlines: Acme Corp, Nexus Inc.
SENTINEL::DISPATCH -> Executive Briefing emailed to leadership team ✓
Autonomous State: ActiveStatus 200 OK
04

DeepCausal™

Multi-Hypothesis Root-Cause Investigator

Deep Analytical ReasoningIN PROGRESS

How It Operates in Decyra

Traditional dashboards tell you *what* happened, but leave you guessing *why* it happened. When an operator asks 'Why did gross margin drop last month?', DeepCausal autonomously spins up 3 parallel hypothesis sub-queries: segmenting by product SKU, inspecting supplier price increases, and analyzing sales discount trends. It correlates the variance across all three dimensions to deliver an undeniable root-cause answer in plain English.

Execution Protocol Steps
  • 1Detects analytical investigatory intent ('Why', 'Cause', 'Driver', 'Spike', 'Drop').
  • 2Generates 3 parallel analytical hypotheses across distinct dimensions.
  • 3Executes sub-queries concurrently across in-memory data tables.
  • 4Variance correlation engine isolates primary driver and quantifies its contribution.
Business Impact

Replaces 3 days of back-and-forth ticket requests to the data team with a 3-second definitive answer.

Defensible Moat

Solves the core deficiency of legacy business intelligence (Tableau, PowerBI), creating an unassailable enterprise product moat.

Agent Execution Stream
Groq LPU Runtime
USER_PROMPT -> "Why did net expansion drop in Q3?"
DEEPCAUSAL::HYPOTHESIS_1 [Cohort Churn] -> Flat (0.2% variance)
DEEPCAUSAL::HYPOTHESIS_2 [Tier Downgrades] -> Spike in Tier-2 to Tier-1 (-18% variance)
DEEPCAUSAL::SYNTHESIS -> Primary driver: Mid-market seat contraction post-merger.
Autonomous State: ActiveStatus 200 OK
05

SchemaPilot™

Proactive Contextual Discovery Agent

Self-Serve Operator GuidanceFUTURE IMPLEMENTATION

How It Operates in Decyra

When users connect a new 300-table Snowflake warehouse or a complex ERP database, they rarely know where to begin. SchemaPilot analyzes table relationships, primary/foreign keys, and data densities to construct an interactive topological map. It then auto-generates high-value operational business questions tailored specifically to the company's business model.

Execution Protocol Steps
  • 1Inspects database schema topology and infers business entity relationships.
  • 2Identifies key metric tables (Orders, Customers, Invoices, Subscriptions, Churn).
  • 3Formulates curated, high-impact business questions tailored to the industry.
  • 4Guides operators through 1-click exploratory queries with suggested follow-ups.
Business Impact

Enables non-technical users to generate value from enterprise data immediately without requiring documentation or training sessions.

Defensible Moat

Slashes enterprise time-to-value (TTV) from 45 days to under 5 minutes, unlocking rapid viral expansion within client organizations.

Agent Execution Stream
Groq LPU Runtime
SCHEMAPILOT::TOPOLOGY_SCAN -> 184 tables detected across 4 schemas
SCHEMAPILOT::IDENTIFIED_DOMAINS -> Billing (Stripe), Sales (PostgreSQL), CRM (Salesforce)
SCHEMAPILOT::RECOMMENDED_PROMPT -> "Track customer cohort LTV by acquisition channel"
Autonomous State: ActiveStatus 200 OK
06

Sonictra™

Multi-Modal Conversational Voice Agent

Multi-Modal Voice & SynthesisLIVE

How It Operates in Decyra

Sonictra enables operators to interact with complex enterprise data completely hands-free. Using proprietary real-time streaming audio transcription and multilingual intent parsing, executives can speak naturally in English, Arabic, Spanish, French, Japanese, or German. Sonictra transcribes the audio, grounds the SQL logic, queries the database, and speaks the plain-English insight back out loud in real time.

Execution Protocol Steps
  • 1Browser audio streaming captures voice query in high-fidelity Opus format.
  • 2Real-time multilingual transcription engine parses operational intent.
  • 3Groq LPU reasoning model generates schema-grounded ANSI SQL query.
  • 4Answer is rendered visually in data tables and synthesized into natural spoken voice.
Business Impact

Designed for traveling executives, field sales leaders, and operators who need immediate answers between meetings or while commuting.

Defensible Moat

Enterprise-grade multilingual support (including RTL Arabic) unlocks major global contracts in the Middle East, Europe, and Asia-Pacific.

Agent Execution Stream
Groq LPU Runtime
SONICTRA::AUDIO_INPUT -> Stream received (Arabic: 'ما هي أعلى الصفقات المبرمة هذا الشهر؟')
SONICTRA::TRANSCRIBE_INTENT -> "What are the top closed deals this month?"
SONICTRA::QUERY_EXEC -> Found 4 deals totaling $620,000
SONICTRA::VOICE_SYNTHESIS -> Audio output streaming completed in 420ms ✓
Autonomous State: ActiveStatus 200 OK

Category Comparison

Why Legacy Chatbot Wrappers Fail in Enterprise Analytics

CapabilityTraditional ChatbotsThe Decyra Agentic AI Suite
Error HandlingCrashes with SQL syntax error; forces user to debug.Auto-Healing SQL traps errors, reflects on engine trace, and auto-corrects in 25ms.
Data PrivacyUploads database rows to third-party cloud servers.Decyra Vault guarantees 100% in-browser RAM execution; zero customer records stored.
Explaining 'Why'Returns single flat number; requires 5 manual follow-up questions.DeepCausal runs 3 parallel sub-queries to isolate the exact cohort/product driver.
ProactivityPassive: Does nothing until human types a prompt.Sentinel proactively evaluates 30-day baselines at 7:30 AM and emails morning briefs.

Deploy Decyra's Autonomous Agents Across Your Data Stack

Experience the power of Zero-Egress Vault privacy, Auto-Healing SQL, and 24/7 Sentinel anomaly alerts with your real data.