Runtime Stability Without Model Access
Runtime Stability Instrumentation - Without Model Access
Integration Principles
FieldLock is designed to integrate into production AI systems without altering how they work.
Four constraints govern every deployment:
No access to model internals
No weights, gradients, hidden states, or training dataRead-only by default
Measurement precedes any discussion of controlProvider-agnostic compatibility
Works across closed APIs and open modelsMinimal operational footprint
No changes to your serving stack or workflows
These constraints are intentional.
They preserve scientific integrity, governance feasibility, and operational safety.
Supported Integration Modes
FieldLock supports multiple deployment patterns to match risk tolerance and environment constraints.
Inline Proxy Mode
Observes outputs as they are emitted
Suitable for agentic and long-horizon systems
Negligible latency impact (read-only capture)
Sidecar / Mirror Mode
Asynchronous mirroring of inference outputs
Zero impact on live traffic
Common in regulated or staged environments
Log Replay / Offline Mode
Ingests recorded inference logs
Enables forensic analysis and baseline comparison
Used for pilots, audits, and post-incident review
What FieldLock Reads
FieldLock ingests output-level telemetry only, such as:
token sequences
timing and sequencing information
turn and session boundaries
recursion and tool-call structure (when present)
It does not require:
prompt inspection for meaning
semantic labeling
task-specific tuning
What FieldLock Produces
FieldLock produces runtime stability artifacts, not model judgments.
1. Stability Signals
Continuous indicators derived from inference behavior over time.
2. Regime Classification
Each run is classified into canonical runtime regimes:
Stable
Transitional
Phase-Locked
Collapse
Recovery
These describe behavioral dynamics, not output quality.
3. ESL Reports
Portable, governance-ready artifacts that include:
regime timelines
instability events
lead-time to failure
risk tier classification
Reports can be exported in structured formats for:
audits
governance review
comparison across systems
Security & Compliance Posture
FieldLock is built for enterprise and regulated environments.
No exposure of model IP
No training data ingestion
No prompt retention by default
Deployment supports:
VPC and private cloud
on-prem and isolated environments
configurable data handling and retention policies
Compatibility
Because FieldLock operates on runtime behavior, not architecture, compatibility does not depend on model family.
It has been validated across:
closed API models
open-source deployments
non-transformer dynamical systems
This ensures long-term survivability as models evolve.
Why Output-Only Matters
Output-only integration is not a limitation.
It is what makes FieldLock:
portable across vendors
acceptable to regulators
deployable without negotiation over IP
resilient to future model changes
FieldLock measures motion, not machinery.
Operational Impact
No retraining required
No prompt changes required
No serving stack modification
Can be enabled or disabled without disruption
FieldLock integrates like observability — not like control.

