The Governed Agentic SDLC
Stop guessing with ungoverned AI outputs. We bring deterministic quality, telemetry tracking, and strict Human-in-the-Loop governance to the software lifecycle.
Why 90% of AI Pilots Fail in Production
Enterprise software demands deterministic guarantees. Here is the chronological failure path of ungoverned AI pilots:
Blind Spot Architecture
LLMs are tasked with making autonomous decisions on partial system views, causing unpredictable downstream architectural breakages.
Context Window Saturation
Shoving massive codebases into token windows causes "lost in the middle" attention drift, token bloat, and hallucination spikes.
Non-Deterministic Execution
Relying on loose text outputs rather than compiled, type-safe JSON schemas eventually produces broken API payloads.
Silent Output Drift
Model logic subtly degrades across prompt updates. Without active telemetry, teams have zero visibility into accuracy loss.
The LLM Architecture Audit
We drop a seasoned architectural team into your environment to benchmark your AI implementations against deterministic standards. We don't guess — we measure.
Codebase & Prompt Review
Line-by-line analysis of your context mapping, retrieval chunks, and prompt schemas.
Telemetry Injection
We inject our proprietary tracking to establish baseline hallucination rates and latency metrics.
Drift Measurement
Evaluating how your responses change over time under production scale.
Governance Scorecard
A 20-page comprehensive report outlining exactly why the application breaks and how much token waste is occurring.
Remediation Roadmap
A precise, step-by-step engineering plan to achieve deterministic stability.
Executive Decision Checkpoint
Aligning technical debt with business costs to greenlight the repair phase.
Governed Agentic Development
Our dedicated Agentic developers execute the remediation roadmap. We decouple reasoning models from retrieval streams, creating highly resilient systems.
Graph-RAG Indexing
Replacing naive vector search with dependency-aware AST RAG to stop context window bloating.
Deterministic Prompt Engine
Moving from loose generative vibes to strictly compiled, typed, and guaranteed inference outputs.
Agent Protocol Setup
Establishing binary-encoded communications between multi-agent systems for speed.
Guardrail Enforcement
Hardcoded governance policies ensuring models never break safety or schema bounds.
Continuous Validation
Every commit runs against a suite of synthetic validation prompts to guarantee zero drift.
Zero-Downtime Deployment
Rolling out the fixed architecture side-by-side with your existing legacy AI for safe transitioning.
Is your AI failing in production?
Stop guessing. Our deterministic LLM Governance Audit benchmarks your RAG pipelines against 6 strict production standards to identify hallucination vectors and context window leaks.
- Prompt Compilation Assessment
- Telemetry Drift Analysis
- 20-Page Governance Report Card