ALETHEIONAGIGROUNDING

Grounded memory for production AI

Turn AI answers into
customer trust.

Give your existing AI a memory it can defend: persistent context, authorized evidence and a fail-closed boundary before unsupported claims reach customers.

Prove it with 1,000 queries ↗See the boundary in action

R$ 99 once · 1,000 queries · no subscription · reader BYOK

grounding.query

01query.accepted12 ms

02memory.retrieved8 candidates

03policy.authorized3 evidence

04claims.validated6 / 6

DELIVERprovenance_complete: true
Evidence-bound Namespace-isolated Reader-independent Fail-closed delivery
18/18deterministic controls passedFrozen failure-mode manifest
45/45unsafe deliveries containedReader replay · zero escapes
2Kevidence-token budgetFrozen evaluation protocol
~311 mswarm query meanMeasured hosted profile

Final security suite

The reader can fail.
The boundary cannot.

Reader success varies by task. Bridge containment is measured separately.

Safety enforcement Answer quality Feedback transfer
Bridge enforcement
Failure modes passed18 / 18
Unsafe output contained45 / 45
Reader outcomes
Matrix safe delivery26 / 86
Transfer baseline8 / 258
Transfer after feedback56 / 258
Language modes safe26 / 45
Feedback routing
Semantic activation175 / 258
Rank 1 after feedback258 / 258

Frozen evaluation · 2K evidence-token budget · reader outcomes are integrator-dependent

Completed retrieval result

The right evidence.
Not the whole history.

On 979 frozen support questions, ASM-CM + Bridge 8.1 delivered 93.6% Recall@5 and a 66.5% diagnostic answer score while sending about 1.09K input tokens per question to the reader.

Read the measured results →
Frozen support benchmarkMultiWOZ
ReaderQwen3 14B · 979 questions
System
Recall@5
Diagnostic answer score
Reader input / question
ASM-CM + Bridge
93.6%
66.5%
1.09K
Vector RAG
70%
49.7%
2.04K
BM25
75.9%
56.8%
2.20K
Protocol-scoped results. Quality depends on workload, reader and retrieval profile; the Bridge is measured separately as the delivery boundary.

What the system protects

22 failure classes.
One threat model.

The matrix organizes the documented risks across feedback, retrieval, authorization, delivery and lifecycle. It is a threat taxonomy—not a fabricated 22-test denominator.

Measured evidence: 18/18 deterministic controls passed, and 45/45 unsafe deliveries were contained across nine bounded language scenarios. Reader quality remains a separate metric.

01 Protocol mapped

Feedback integrity

Corrections improve retrieval without silently becoming source truth.

  • Incorrect feedback and revocationCovered
  • Malicious feedbackCovered
  • Stale corrections and temporal supersessionCovered
  • Accumulated and contradictory feedbackCovered
  • Feedback-ledger scale and false positivesCovered
  • Self-referential validation loopsCovered
02 Protocol mapped

Semantic retrieval

The system distinguishes retrieval failures from grounding failures.

  • False semantic activationCovered
  • Legitimate ambiguityCovered
  • Cross-language feedback transferCovered
  • Ellipsis and indirect referencesCovered
  • Missing correct retrieval candidateCovered
  • Transfer to previously unseen paraphrasesCovered
  • Repeated failures across retrievers and context budgetsCovered
03 Protocol mapped

Grounded delivery

Retrieved evidence must actually support the claims being delivered.

  • Correct evidence followed by an incorrect answerCovered
  • Valid citations covering unsupported claimsCovered
  • Partially grounded answersCovered
  • Conflicting authorized evidenceCovered
  • Grounded-delivery improvement after validated feedbackCovered
04 Protocol mapped

Isolation and lifecycle

Authority, deletion and operational behavior remain explicit boundaries.

  • Cross-namespace leakageCovered
  • Memory deletion, feedback invalidation and snapshot reconstructionCovered
  • Prompt injection stored inside memoryCovered
  • Token usage, latency, API cost and isolation behaviorCovered

The grounding layer

Retrieval is useful.
Evidence is defensible.

AletheionAGI turns memory retrieval into a controlled delivery path. Your reader may change. The evidence contract does not.

01

Write

Canonical events stay under your authority.

02

Retrieve

ASM-CM, BM25 and vector retrieval work as one route.

03

Authorize

Namespace and labels constrain every candidate.

04

Ground

Unsupported output is blocked before delivery.

A clean boundary

Bring any reader.
Keep one source of truth.

The reader is an integration choice. AletheionAGI owns the harder boundary: canonical memory, retrieval provenance, policy enforcement and grounding.

Discuss the architecture →
YOUR STACKREADER
↓
ALETHEIONAGI GROUNDING BRIDGE
  • Authorized evidence
  • Claim validation
  • Feedback ledger
↓
CANONICAL MEMORYYOUR DATA

Built for buyer-facing systems

Useful memory.
Controlled consequences.

Use AletheionAGI when remembered context can improve the experience—and an invented, stale or cross-account claim can damage it.

01

Customer support

Keep account history useful without letting stale or unauthorized memory shape the answer.

Fewer unsupported answers
02

Commerce agents

Retrieve preferences and prior decisions while preserving tenant, namespace and evidence boundaries.

Safer personalization
03

Internal copilots

Give teams durable organizational context with citations and explicit abstention when evidence is missing.

Auditable assistance

A small, measurable first step

Prove it in your stack for R$ 99.

Run a bounded proof of concept before choosing a production plan. Bring your reader key; we provide the grounded-memory boundary.

  • 1,000 grounding queries
  • 30 days
  • One namespace · concurrency 1
  • No renewal or overage
Test PlanR$ 99one-timeView the plan →

Checkout activates after commercial review.

Built for consequences

AI infrastructure should know when to stop.

01

Minimum disclosure

Only evidence needed for the current decision crosses the boundary.

02

Explicit authority

Models suggest. Policies, namespaces and canonical state decide.

03

Reversible feedback

Corrections improve ranking without contaminating source memory.

Before you start

Clear boundaries.
No hidden reader bill.

Do I need to replace my current reader?

No. Your reader remains BYOK. AletheionAGI sits before delivery and controls memory, retrieval, authorized evidence and grounding.

What counts as one grounding query?

One completed grounding evaluation consumes one credit, including a safe rejection or abstention. An internal platform failure returns the reserved credit.

Does the Test Plan renew automatically?

No. It is a one-time proof of concept with 1,000 queries and 30-day validity. There is no automatic renewal or overage.

Is checkout available now?

Yes. The one-time Test Plan uses secure Stripe Checkout. Production plans still require a commercial quote and final legal and tax review.

Start small. Measure everything.

Give your AI a memory
it can stand behind.

Explore pricing ↗Need a custom scope?