Governance • Execution • Trust

BlazeXL:
Governed Runtime for Enterprise Decisions

Enabling deterministic, auditable execution across Excel, Web, AI Agents and more.

Transform fragmented human and AI-generated logic into governed, auditable enterprise assets.
Publish once → Run Everywhere → Govern Always
Platform Overview
Compute GridScalable Python Runtime
Governance GatewaySecurity • Logic • Orchestration
Excel
Blaze App
AI Analyst
The Governance Gap

Business Logic Breaks at Scale

As enterprises accelerate automation, the logic driving critical decisions remains hidden, unmanaged, and unverifiable.

Shadow Logic Is Everywhere

Critical business logic lives in spreadsheets, notebooks, scripts, and prompts — created locally, copied endlessly, and never governed.

Agentic Era Compounds Risk

AI and agentic tools accelerate logic creation, great for exploration but probabilistic and unverifiable.

Modern Data Stack Stops Short

Cloud data platforms govern data and infrastructure, not execution. The logic driving decisions still runs outside enterprise controls.

The Operational Outcome

Teams are forced to choose between speed and trust.

Or accept growing operational and decision risk. Every unmanaged script becomes a liability. Every unverifiable AI output compounds exposure.

Historical Choice
Static Governance
The Future
Governed Execution
The BlazeXL Solution

A Governed Scalable Grounded
Execution Layer

BlazeXL decouples logic from the interface. Use AI to accelerate exploration, build once in Python, manage centrally, and execute anywhere.

Deterministic Engine
Interfaces change. Logic stays verified.
Published once → Governed everywhere

1. Cloud-Native Compute

High-performance Python runtime environment with instant parallelization. Execute complex models across scalable workers in seconds.

ScalableDefense-in-Depth SecurityAdvanced Data Handling

2. Governance Gateway

The BRAIN of the platform. Manages versioning, permissions, and security. Ensures every calculation is deterministic and 100% auditable.

Immutable versioningIdentity-based accessFull audit logs

3. Universal Surfaces

Interchangeable entry points. Use the familiar Excel interface, raw data in our web dashboard, or our AI Analyst to trigger the business logic.

ExcelBlaze AppsAI AnalystAgentsAPI
Single Click Deployment

Blueprints —
Preview Blaze Apps

See what Blaze Apps can do with quick visualization. Build complex logic once (optimizations, visualizations, models), then run anywhere with one click - powered by BlazeXL runtime.

Write Once
Pure Python logic
Immutable
Never-break versioning
Shareable
Instant deployment
Interactive
Rich 3D & 2D viz
LIVE COMPUTE DEMO

See the Power in Real-Time

Our BlazeXL engine bridges Python heavy-lifting with spreadsheet-like speed. Run these live Blueprints to see it in action — no account required.

Governance Layer • Interactive Demo

Eliminate Shadow Logic.

With BlazeXL - every logic fragment is versioned. Every execution is logged. Every hash is verifiable. Watch the full lifecycle.

Step 1Draft Block

Create

An analyst writes a pricing function. BlazeXL captures it as a governed Blaze Block — not hidden in a spreadsheet formula.

Draft v1
Mar 5, 06:01 AM
sha256:9f3a7b2c4e6...
1def price(quantity, unit_price=10):
2 """Calculate total price for an order."""
3 return quantity * unit_price
Initial release — simple quantity × unit_price calculation

Logic is captured as code, not hidden in a formula bar.

pricing_model

Standard pricing logic for order calculations

Private
Provenance
Owner
Sarah Chen
Created
Mar 5, 2026
Status
DRAFT (v1)
Integrity
sha256:9f3a7b2c4e6d8a1...
Exports
price()
Audit Trail
1 events
block.create06:00:00
success
Sarah Chenpricing_model
code_size:98function_count:1status:draftprocessing_purpose:analytics
AI Analyst • Interactive Demo

Ask. Analyze. Govern.

AI generates the code. BlazeXL's deterministic runtime executes it. Every result is auditable, reproducible, and governed.

AI Analyst

Neural Active
|ref:demo_quarterly_sales|
12,400 × 8
👋 I'm your BlazeXL AI Analyst. I've indexed quarterly_sales_2024 (12,400 × 8). I can help you transform this data or build a visualization.

Try a Quick Action below to get started!
Ask about your data...
How It Works

Ask in Plain English

Describe the analysis you need — no code required

AI Generates Logic

The AI writes optimized, auditable Python code

Deterministic Execution

BlazeXL runs it — same inputs always produce same outputs

Full Audit Trail

Code hash, execution ID, and result — all governed

Dataset Schema
datedatetime64
2024-03-15
regionstr
North America
product_linestr
Enterprise
revenuefloat64
1,245,000
units_soldint64
3,420
costfloat64
890,000
margin_pctfloat64
28.5
quarterstr
Q1-2024
Total Size12,400 rows × 8 cols

“AI generates. BlazeXL governs. Every analysis is reproducible.”

Agent Trust Layer • Interactive Demo

What did the agent actually do?

AI agents call governed Blocks — every computation is versioned, audited, and reproducible. The trust layer you need for production AI.

LangChain · Autonomous Agentfinance-ops-agent

Analyze Q4 procurement spend across all departments. Flag any category exceeding quarterly thresholds and determine approval requirements.

Q4 2024 Procurement Ledger (14,200 transactions)
Agent Workflow
Task Received
Classify Spend
Agent Reasons
Check Approval Policy
Agent Reasons
Report Generated
Audit Trail

Start the workflow to see audit events accumulate

“We're not governing the AI's reasoning — we're governing its execution. Every tool call is versioned, audited, and reproducible.”

Compliance Dashboard • Interactive Demo

Compliance in one query.

“Show me every execution of our pricing model in the last 30 days — who ran it, which version, and whether it was a human or AI agent.”

32 events
30 success
2 errors
org-acme-001 · Last 30 days
ActionActorBlockCode HashDurationSurfaceStatus
block.executeMar 15 06:00 PM
sarah.chen
@acme/pricing-modelv1
sha256:852fc9630da780ms
Excel
OK
block.executeMar 15 11:00 AM
james.wilson
@acme/risk-classifierv2
sha256:fc9630da741e117ms
Web
OK
block.executeMar 14 04:00 AM
maya.verma
@acme/spend-analyzerv1
sha256:630da741eb85154ms
API
OK
block.executeMar 12 09:00 PM
finance-ops-agent
@acme/approval-policyv2
sha256:da741eb852fc191ms
Agent
OK
block.publishMar 12 02:00 PM
risk-monitor-agent
@acme/fx-converterv1
sha256:41eb852fc963228ms
Agent
OK
agent.task.completedMar 11 07:00 AM
nightly-batch-agent
@acme/portfolio-rebalancerv1
sha256:b852fc9630da265ms
Agent
OK
block.executeMar 10 12:00 AM
sarah.chen
@acme/pricing-modelv1
sha256:2fc9630da741302ms
API
OK
agent.task.completedMar 9 05:00 PM
james.wilson
@acme/risk-classifierv2
sha256:9630da741eb8
AI An
Error
block.executeMar 8 10:00 AM
maya.verma
@acme/spend-analyzerv1
sha256:0da741eb852f376ms
Excel
OK
block.executeMar 7 03:00 AM
finance-ops-agent
@acme/approval-policyv2
sha256:741eb852fc96413ms
Agent
OK
agent.task.completedMar 5 08:00 PM
risk-monitor-agent
@acme/fx-converterv3
sha256:eb852fc9630d450ms
Agent
OK
block.executeMar 5 01:00 PM
nightly-batch-agent
@acme/portfolio-rebalancerv1
sha256:52fc9630da7487ms
Agent
OK
block.publishMar 4 06:00 AM
sarah.chen
@acme/pricing-modelv1
sha256:c9630da741eb124ms
Excel
OK
app.executeMar 2 11:00 PM
james.wilson
@acme/risk-classifierv2
sha256:30da741eb852161ms
Web
OK
block.executeMar 2 04:00 PM
maya.verma
@acme/spend-analyzerv1
sha256:a741eb852fc9198ms
API
OK
agent.task.completedMar 1 09:00 AM
finance-ops-agent
@acme/approval-policyv2
sha256:1eb852fc9630235ms
Agent
OK
block.executeFeb 29 02:00 AM
risk-monitor-agent
@acme/fx-converterv1
sha256:852fc9630da7272ms
Agent
OK
block.executeFeb 27 07:00 PM
nightly-batch-agent
@acme/portfolio-rebalancerv1
sha256:fc9630da741e309ms
Agent
OK
block.executeFeb 27 12:00 PM
sarah.chen
@acme/pricing-modelv1
sha256:630da741eb85346ms
API
OK
block.executeFeb 26 05:00 AM
james.wilson
@acme/risk-classifierv2
sha256:da741eb852fc383ms
AI An
OK
app.executeFeb 25 03:00 PM
finance-ops-agent
@acme/approval-policyv2
sha256:b852fc9630da457ms
Agent
OK
block.publishFeb 24 10:00 PM
maya.verma
@acme/spend-analyzerv1
sha256:41eb852fc963420ms
Excel
OK
block.executeFeb 24 08:00 AM
risk-monitor-agent
@acme/fx-converterv3
sha256:2fc9630da741
Agent
Error
agent.task.completedFeb 23 01:00 AM
nightly-batch-agent
@acme/portfolio-rebalancerv1
sha256:9630da741eb8131ms
Agent
OK
block.executeFeb 22 06:00 PM
sarah.chen
@acme/pricing-modelv1
sha256:0da741eb852f168ms
Excel
OK
block.executeFeb 21 11:00 AM
james.wilson
@acme/risk-classifierv2
sha256:741eb852fc96205ms
Web
OK
block.executeFeb 20 04:00 AM
maya.verma
@acme/spend-analyzerv1
sha256:eb852fc9630d242ms
API
OK
block.executeFeb 18 09:00 PM
finance-ops-agent
@acme/approval-policyv2
sha256:52fc9630da74279ms
Agent
OK
block.publishFeb 18 02:00 PM
risk-monitor-agent
@acme/fx-converterv1
sha256:c9630da741eb316ms
Agent
OK
app.executeFeb 17 07:00 AM
nightly-batch-agent
@acme/portfolio-rebalancerv1
sha256:30da741eb852353ms
Agent
OK
block.executeFeb 16 12:00 AM
sarah.chen
@acme/pricing-modelv1
sha256:a741eb852fc9390ms
API
OK
agent.task.completedFeb 15 05:00 PM
james.wilson
@acme/risk-classifierv2
sha256:1eb852fc9630427ms
AI An
OK

“Every version locked, execution logged and actor identified. SOC 2, EU AI Act, GDPR Art. 22 — covered.”

Platform Compounding • Interactive Demo

Write once. Run everywhere.

A Block (Python logic fragment) written once is automatically available in Excel, AI Agents and more — without being rewritten. Audit trail built-in.

Surface Network
Blockpricing:v3
Central Block
Name@org/pricing-model:v3
Ownersales-team
Hashsha256:9f86d081884c7
Total Executions14,280

Click a surface node or press “Connect Surfaces” to see how the block is consumed

0Surfaces
1Block
1Audit Trail

“Every new surface multiplies the value of every existing Block. That's the compounding asset.”

The Blaze Stack

Three Layers.
One Governed Workflow.

From logic creation to enterprise distribution.

Blaze Blocks

The immutable, version-locked source of truth for logic. Build once in Python, deploy everywhere.

Blaze Apps

Governed web interfaces powered by the Compute Grid. Deliver interactive logic to stakeholders in seconds.

Blaze Sheets

Lightweight spreadsheet artifacts for power users. All the power of Excel, backed by governed cloud logic.

Data Layer
Agnostic Runtime.

BlazeXL separates logic from storage. Keep your data where it lives—Snowflake, S3, or Postgres—and execute logic with zero persistence.

S3SnowflakePostgresAPI JSON

Data Agnostic

Data stays in your existing S3, Snowflake, or Postgres. BlazeXL never stores your raw data permanently.

Ephemeral Load

Data is loaded into session-based memory, optimized for high-performance execution, then wiped.

Logic Governance

Focus exclusively on governing the logic and execution. We provide the runtime; you keep the data.

Scalable Execution
Infrastructure Power

BlazeXL isn't just a wrapper. We maintain a high-performance compute grid that handles governed execution with sub-second latency.

Standard ExcelLimited
Excel + NotebooksFragile
BlazeXL EngineGoverned & Scalable
Instant
Parallel Calcs
Low Latency
100%
Python Native
No translation lag
Managed
Consistent
Ready-to-run grid
Audit-Ready
Signed Logs
Deterministic hash
Enterprise Governance

Trust Is Non-Negotiable

Most AI tools rely on probabilistic inference — powerful for exploration, fragile for execution. BlazeXL uses AI where it excels, then executes verified logic deterministically.

Capability
Generic AI Execution
BlazeXL Platform
Execution Model
Probabilistic Inference (LLM)
Deterministic Runtime
Accuracy
Requires Human Verification
Verifiable Logic
Audit Trails
Limited to prompt/session context
Full Immutable Logs
Parallel Scaling
No native parallel execution model
Scalable Parallel Workers
Data Governance
Chat-based / Transient
Identity-Managed Access

Secure Compute

Ephemeral, isolated workers shred data after every execution. Your proprietary data is encrypted in transit and at rest.

Logic Provenance

Logic units are version-locked and immutable. Audit exactly which code ran, who authorized it, and when.