Context Correctness Runtime

Fresh context for agents that cannot afford to be wrong.

KyroDB sits between your AI agents and changing knowledge stores, enforcing freshness, scope isolation, provenance, and proof on every retrieval.

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WATCH KYRODB IN ACTIONINTEGRATE RUNTIME

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KyroDB Runtime >

RUNTIME_CONFIG

TENANTacme-corp

NAMESPACEsupport/billing

FRESHNESSstrict

CONTEXT_RETRIEVAL_PIPELINEstatus: PROCESSING

FETCH & VALIDATE CONTEXTpid:1024

# Initializing context runtime
ctx = run_kyrodb_tool(
  'VECTOR_SEARCH',
  namespace='support/billing'
)
for doc in ctx.results:
  proof = validate_freshness(
    doc, 
    policy='strict'
  )

INSTANCE-1processing

# Enforcing boundaries
bounds = run_kyrodb_tool(
  'CHECK_SCOPE',
  tenant='acme-corp'
)
if bounds.safe:
  # context packet assembled
  # proceed to generation

The real agent failure

Better models amplify good context. They cannot invent it.

Most production mistakes are not "the model is dumb." They are caused by incomplete, stale, unsafe, or untraceable evidence arriving before the model acts.

Stale state

An agent answers from last hour's policy even after a change was acknowledged.

Wrong scope

The right document leaks through the wrong tenant, branch, role, or entitlement.

Missing evidence

The model reasons well, but never saw the migration, test, ticket, or trace that mattered.

No proof

A failure happens in production and nobody can explain which context was used or why.

Agent

KyroDB Runtime

Knowledge stores

Proof plane

How it works

Observe change. Resolve scope. Return proof.

KyroDB gives agents a small, enforceable context contract instead of a bigger pile of retrieved text.

01Connect existing stores.

02Track freshness boundaries.

03Block wrong-scope context.

04Emit packet plus proof.

01change

02scope

03retrieve

04prove

ContextPacketfresh / scoped / proven

Product surface

A runtime contract, not a prettier search response.

Each response carries only the evidence an agent can safely use.

KyroDBcontext plane

freshgeneration ok

scopetenant locked

source5 docs

prooftrace bound

Freshness-aware retrieval

Strict reads never silently serve context older than the acknowledged generation.

Scope-safe reuse

Cache hits are partitioned by tenant, auth, policy, filters, model pins, and generation.

Context proofs

Every packet maps back to an enforcement boundary or explicitly admits best effort.

Trace and diagnosis

Every retrieval emits evidence for why context was included, omitted, blocked, or degraded.

Replay and shadow gates

Teams can compare candidate behavior before traffic moves to production.

Embed-safe runtime

Rust embedders use the same auth, limits, rate limits, evidence, and serving semantics.

Built for teams where stale context becomes a product incident.

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Production support agentsEnterprise copilotsAI coding contextVoice and realtime agentsProduction support agentsEnterprise copilotsAI coding contextVoice and realtime agents

Evidence before trust

See proof before you cut over.

Separate freshness, relevance, availability, and scope incidents before they become production incidents.

View evidence workflows

shadow-run / candidatehealthy

OK matched 1,024 captured retrievals

OK zero scope incidents

OK stale baseline blocked by candidate

! 4 relevance regressions require review

proof_bundle.jsonredacted

Build with the runtime

Your agent should know when it knows.

And refuse to guess when context is stale, unsafe, or unprovable.

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