Agent Control
Designing policy layers, permissions, and deterministic gates.
SYPerith | Apex
Engineering Advisory for Governed AI Systems.
Meta Description
Specialized engineering advisory for agentic and retrieval systems. We focus on bounded execution, defensible evaluation, and temporal correctness under production latency and cost constraints.
The Mission
AI that remains correct after deployment.
Most production failures are not model failures; they are boundary failures. When intent becomes action without policy, or tools execute without constraints, systems become liabilities.
Apex focuses on hardening these boundaries. We turn probabilistic output into governable software by enforcing strict controls on agency, retrieval validity, and evaluation logic.
Core Focus Areas
System Evaluation
Building harnesses that withstand gaming and distribution shift.
Temporal Correctness
Ensuring retrieval respects validity windows, provenance, and time.
Production Envelopes
Managing cost and latency without compromising reliability.
Background & Context
- Evaluation Systems: Built modular rubric systems for generative outputs (Outlier AI).
- Constrained Research: Delivered metric-constrained research under high performance pressure (WorldQuant).
- Public Engineering: Architected ChronoRAG and TimeGuard GraphRAG for time-aware retrieval.
Failure Surfaces
We target specific, high-risk failure modes that standard integration often overlooks:
1. Unbounded Agency
The Issue
Tools executing side effects without explicit constraints (permission sprawl, implicit goals).
The Fix
Strict boundary definitions and stop conditions.
2. Indefensible Evaluation
The Issue
Measuring “answer quality” while missing invalid logic paths or silent failures.
The Fix
Evaluation rubrics that penalize reasoning errors, not just final output.
3. Temporal Inconsistency
The Issue
Semantically correct answers that are historically invalid.
The Fix
Time-aware retrieval logic and validity window enforcement.
4. Post‑Deployment Drift
The Issue
Input patterns shift and data freshness decays, causing silent degradation.
The Fix
Continuous measurement loops to detect drift before incidents.
Engineering Doctrine
Interfaces over Components
Reliability is designed at the boundary. The flow from Intent → Policy → Execution must be explicit and monitored.
Correctness ≠ Plausibility
A plausible answer without traceable validity is a hallucination.
Determinism at Control Points
Probabilistic models propose. Deterministic constraints decide.
Time is a Contract
Retrieval must respect time, provenance, and recency guarantees.
Cost is a Safety Metric
Systems that ignore latency and budget constraints fail under pressure.
Engagement Method
Apex is an engineering engagement focused on proof, boundaries, and measurement.
Phase 1 — Boundary Audit
System mapped as an execution graph: inputs, tools, policies, failure propagation.
Phase 2 — Reliability Modeling
Correctness defined through invariants, forbidden actions, and escalation protocols.
Phase 3 — Evaluation Control Loop
Continuous harness: scenario suites, adversarial testing, regression gates.
Phase 4 — Governance Hardening
Permission layers, deterministic validation, traceable provenance logs.
Work Product
Artifacts designed to be versioned, enforced, and owned by engineering teams.
Control Boundary Spec — Intent, policy, tool constraints, stop conditions.
Evaluation Harness — Scenarios, scoring rules, regression gates.
Temporal Correctness Contract — Validity, recency, provenance enforcement.
Failure Register — Ranked by blast radius, likelihood, cost-to-fix.
Cost/Latency Envelope — Routing and budget rules that preserve correctness.
Technical Anchors
ChronoRAG
https://github.com/SSKG2602/chronorag
Temporal retrieval architecture enforcing validity windows and historical consistency.
TimeGuard GraphRAG
https://github.com/SSKG2602/timeguard-graphrag
Constrained graph retrieval with time-gated access paths and strict policy adherence.
Apex Statement
Apex operates strictly as a reliability intervention. Systems authorized to execute actions, handle customer data, or drive decisions depend on architectural enforcement: bounded behavior, defensible evaluation, and measured drift.
Contact
Private Engineering Advisory
Phone
+91 9141175879
GitHub