u/Difficult-Angle-4715

OnTheRice.org

Link to research - https://g.co/gemini/share/6c8296e2b85a

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8 AI models. Scanning the internet simultaneously. Surfacing what the world hasn't noticed yet.

OnTheRice.org tracks emerging products, cultural shifts, demand spikes, and trend signals across 25+ categories — before they reach mainstream awareness.

Not another dashboard. Not another feed. An early warning system for people who need to know first.

Ranked #1 signals platform in breadth and potential. We scan the internet for you daily.

→ ontherice.org

#AI #AiTrends #Signals #News #Singapore

OnTheRice.org

Been quietly building this for quite a while and thought I’d finally share it here.

The idea started because I realised most “trend detection” platforms only notice something after it already becomes obvious. By the time mainstream media talks about it, the signal is usually already mature. I wanted to see if AI could detect smaller movements earlier, while they still look random and disconnected.

So I built an AI engine that constantly scans fresh internet data and tries to figure out whether something is genuinely starting to gain momentum in the real world. Not just social media hype, but actual shifts in attention, demand, behaviour, shortages, public discussion, or emerging narratives.

One of the hardest parts was filtering noise. The internet creates thousands of fake “mini trends” every day that disappear almost immediately. A huge amount of development time went into teaching the system the difference between temporary spikes and signals that continue strengthening across multiple sources over time.

I also didn’t want it to feel like raw analytics dashboards where humans still need to interpret everything themselves. I wanted the output to read more like intelligence briefings in normal English, where the AI explains why something matters and what direction it seems to be moving in.

Under the hood, it uses multiple AI models together instead of relying on a single one. Different models are better at different tasks, so some focus more on extraction, some on classification, some on synthesis, and some on filtering weak signals.

Still a work in progress and still tuning the system constantly, but it’s honestly been fascinating watching it occasionally surface movements before they become widely discussed publicly.

BASE44 BILLING INTEGRITY & UNTRACKED INTEGRATION CREDIT CONSUMPTION REPORT

Prepared by:

OnTheRice

EXECUTIVE SUMMARY

This report documents a repeated pattern of unexplained integration credit consumption within the Base44 platform despite multiple rounds of investigation, mitigation, and claimed resolution.

The issue evolved from an ordinary debugging concern into a broader operational and billing integrity problem after:

- Integration credits continued increasing during inactive periods

- Multiple safeguards were already enabled

- Base44 itself acknowledged architectural gaps allowing certain backend functions to bypass the billing ledger

- The issue continued recurring after multiple declarations that the system was “fully locked” and resolved

The central concern is no longer merely unexpected credit usage.

The core concern is that users may be charged for billable AI activity that is not fully observable, auditable, or represented within the visible ledger system.

This creates a material transparency issue affecting:

- Production reliability

- Cost predictability

- Operational trust

- Deployment confidence

- Platform dependency risk

BACKGROUND

The OnTheRice workspace operates as an AI-driven application environment containing:

- Signal systems

- Discovery systems

- AI orchestration workflows

- Daily Intel Brief systems

- Multi-agent structures

- Publishing pipelines

- Backend functions

- Frontend-triggered workflows

The workspace experienced repeated unexplained increases in integration credit consumption over multiple weeks.

These increases occurred even after:

- Pipelines were disabled

- Kill switches were enabled

- Manual triggers were disabled

- Known LLM invocation paths were blocked

- Multiple AI agents were deleted

- Automations were reviewed and disabled

Despite this, integration credits continued increasing.

CHRONOLOGICAL TIMELINE

13 April 2026

Large unexplained integration credit spikes first observed.

User documented concern regarding:

- Sudden credit depletion

- Unclear source of consumption

- Potential platform-side issue

Approximate visible impact:

- Thousands of credits consumed unexpectedly

14 April 2026

Further reports submitted.

User messages referenced:

- “Integration credits RIP”

- API integration concerns

- Ongoing unexplained burn patterns

Issue remained unresolved.

15–26 April 2026

Repeated concern escalation.

User communications included:

- “We are bleeding integration credits and idk why”

- “Integration became 0 due to a bug”

- Repeated references to unexplained credit depletion

At this stage:

- Issue was already persistent

- Not isolated

- Operational confidence materially affected

Early May 2026

A major investigation phase began.

Multiple Base44 diagnostic sessions attempted to identify the root cause.

Claims made during investigation included:

- Queue executions responsible

- Historical queued engine runs responsible

- Certain frontend pages responsible

- Potential hidden invocation paths

- Backend function bypasses

Several suspected pathways were identified and allegedly fixed.

KEY PLATFORM STATEMENTS

Statement 1:

“The burn is NOT going through invokeLLMGuarded”

Implication:

The standard observable ledger path was not capturing all billable activity.

Statement 2:

“Backend functions that call InvokeLLM directly bypass the ledger”

Implication:

Some invocation pathways were acknowledged to exist outside the primary billing visibility mechanism.

This is the single most important architectural admission in the investigation.

Statement 3:

“Nothing else in your app code can possibly burn integration credits right now. The system is fully locked.”

Implication:

Base44 represented the system as effectively isolated from further burn activity.

However, subsequent credit increases continued.

Statement 4:

“The issue was caused by historical queued executions”

Implication:

The problem was initially framed as historical delayed billing rather than active ongoing consumption.

This explanation became inconsistent after later increases occurred.

TECHNICAL FINDINGS

Finding 1 — Zero Observable Activity

During investigation windows:

- ZERO EngineRun entries observed

- ZERO PublishedFeedItems created

- ZERO SignalRuns created

- ZERO new ledger activity visible

Yet:

- Integration credits continued increasing

This creates a direct contradiction.

Finding 2 — Billing Activity Without Observable Invocation

The platform itself acknowledged that:

- Certain backend calls bypassed the primary ledger path

- Some invocation routes were not fully visible to users

This means users cannot independently verify whether all billed activity corresponds to visible execution activity.

This transforms the issue from debugging into billing auditability.

Finding 3 — Overnight Consumption During Inactivity

Additional evidence later emerged.

Earlier snapshot:

- Integration credits approximately 57.2k / 75k

Later snapshot:

- Integration credits approximately 58.1k / 75k

Increase:

- Approximately 900 additional credits consumed

Observed during:

- Inactive periods

- No intentional user activity

- After prior claims of resolution

This materially weakens earlier conclusions that the issue was fully contained.

CONTRADICTIONS IDENTIFIED

Contradiction A:

Claim: “System fully locked”

Observed reality:

- Credits continued increasing

Contradiction B:

Claim: “Historical queue already completed”

Observed reality:

- Additional overnight increases continued later

Contradiction C:

Claim: “No observable execution activity”

Observed reality:

- Credits still consumed

Contradiction D:

Claim: “Root cause identified and fixed”

Observed reality:

- Repeated recurrence across multiple weeks

OPERATIONAL IMPACT

The issue has caused several operational consequences.

1. Cost Uncertainty

- Budgeting uncertainty

- Deployment hesitation

- Difficulty forecasting operational costs

2. Platform Trust Erosion

Repeated declarations that the issue was fixed followed by continued increases materially reduced operational trust.

3. Production Deployment Risk

The workspace is intended for:

- Public-facing systems

- AI-driven workflows

- Growth-stage deployment

- Potential investor-facing demonstrations

Unobservable billing activity creates deployment risk.

4. Auditability Concerns

The platform acknowledged invocation paths capable of bypassing the visible ledger.

Users may not possess the ability to independently audit all billable activity.

This is the core integrity concern.

ARCHITECTURAL CONCERN

Observable Path:

invokeLLMGuarded

This path:

- Appears logged

- Appears ledger-visible

- Appears monitored

Unobservable Path:

Direct InvokeLLM backend calls

This path was described as capable of:

- Bypassing the ledger

- Creating billable activity outside primary visibility systems

If accurate, this means:

- Metering may not be fully observable

- Billing attribution may not be fully auditable

- Cost analysis may be incomplete

CURRENT STATUS

At the time of this report:

- Integration credits continue increasing intermittently

- Full root cause has not been conclusively demonstrated

- Platform-side review remains ongoing

- Compensation discussion has been opened but not finalized

Base44 support acknowledged:

- Architectural transparency concerns

- Possibility of platform-side attribution review

- Potential compensation pathway

However:

No definitive guarantee has yet been provided confirming that ALL billable LLM invocation paths are now fully metered, observable, and auditable.

CORE CONCLUSIONS

Conclusion 1:

This is not a simple isolated bug.

The issue persisted across:

- Multiple weeks

- Multiple investigations

- Multiple claimed fixes

- Multiple mitigation attempts

Conclusion 2:

The platform itself acknowledged the existence of invocation pathways capable of bypassing the visible billing ledger.

This is the most material finding.

Conclusion 3:

The inability to independently verify all billable activity creates a billing integrity issue.

Conclusion 4:

Repeated recurrence after claimed resolution materially weakens confidence in previous remediation attempts.

Conclusion 5:

The issue now affects:

- Operational trust

- Production readiness

- Platform dependency confidence

- Financial predictability

not merely debugging.

REQUESTED ACTIONS

1. Full Billing Audit

Comprehensive review of:

- Integration credit attribution

- All invocation pathways

- Backend-triggered executions

- Historical queue behavior

- Any bypass-capable backend functions

2. Definitive Architectural Clarification

Written clarification regarding:

- Whether any billable paths remain outside observable ledger systems

- Whether all LLM calls are fully auditable

- Whether users can independently reconcile billing with activity

3. Reimbursement Review

Reassessment of:

- Unexplained burns

- Overnight increases

- Post-lockdown consumption

- Historical unexplained spikes

4. Senior Technical Escalation

Review by:

- Senior engineering personnel

- Platform billing teams

- Architecture review personnel

5. Future Billing Safeguards

Implementation of:

- Complete invocation visibility

- User-auditable execution traces

- Transparent billing attribution

- Spend safeguards

- User-side monitoring tools

FINAL STATEMENT

The central issue documented in this report is not simply high AI usage.

The central issue is continued billable integration credit consumption despite incomplete observability into all invocation pathways.

When a platform acknowledges that certain backend calls may bypass the primary ledger visibility system, users lose the ability to independently verify whether all charges correspond to observable execution activity.

That transforms the issue from a debugging concern into a billing transparency and operational trust issue.

This report respectfully requests:

- definitive technical clarification

- complete auditability confirmation

- reimbursement review

- architectural assurance moving forward

Prepared by:

OnTheRice