Reliability. Cost Governance.
Security. Engineered In.
Battle-tested, self-hosted software products and elite asynchronous auditing built to eliminate token bleeding, scale local inference, and enforce absolute compliance across multi-cloud and LLM infrastructure.
Two engagement models. Buy a production-ready software asset and ship today, or commission a 72-hour async audit and receive code patches with zero alignment meetings required.
Buy & Deploy. No Engagement Required.
Discrete, license-based software assets and SaaS tools. Purchase, pull the verified repository, and ship to production independently of any advisory engagement.
Token Sentinel AI Gateway
A lightweight, high-performance API proxy that intercepts all outbound LLM traffic as a transparent layer — enforcing cost governance, routing intelligence, and caching policy without modifying a single line of application code. Built on Go/Bifrost-compatible architecture with an OpenAI-compatible passthrough interface.
Caches static system prompts and repeated context blocks at the gateway layer. Cuts input token bills by up to 90% on cache-hit workloads — zero application code changes.
Rules engine classifies request complexity and automatically routes to SLMs (Claude Haiku, GPT-4o-mini, Gemini Flash) vs. flagship models — configurable per endpoint, team, or cost threshold.
Intercepts non-urgent workloads — bulk embeddings, nightly classification, report generation — and queues them to Batch API endpoints at a fraction of synchronous pricing.
Self-Hosted LLM Runtimes & Private Knowledge Bases
Production-hardened, air-gapped deployment templates that sever dependency on closed-frontier APIs. Every module is pre-wired for GPU-optimized inference, private vector retrieval, and automated PII redaction — delivered as a fully integrated Terraform + Helm package, mergeable into any monorepo, with signed release tags and reproducible builds.
- Continuous batching + tensor parallelism config for A100/H100 GPU node pools
- SGLang RadixAttention KV-cache tuning — maximizes GPU memory utilization
- OpenAI-compatible endpoint via Kubernetes Ingress with mTLS termination
- Supports DeepSeek, Llama 3.x, Qwen 2.5 with full model-weight ownership
- Qdrant, Milvus, or Pinecone deployment with HNSW index and filtered ANN search
- Hybrid retrieval — dense vector + BM25 sparse for precision-recall balance
- Automated PII and secrets redaction filter pipeline before embedding ingestion
- Embedding pipeline observability — p50/p95/p99 latency dashboards per collection
Premium Monetized MCP Servers
Commercial MCP (Model Context Protocol) servers that allow client LLMs — Claude Code, Cursor, or any corporate agent framework — to safely read live infrastructure context without touching raw credentials. Each server runs as an isolated sidecar inside your VPC: raw provider keys scoped exclusively to the MCP process, only sanitized metadata crossing the protocol boundary.
Integration: permissionless via API key tiers or standard bearer token via billing gateway. Compatible with any MCP-aware IDE or agent runtime.
FinOps Billing MCP
Read-only hook into AWS Cost Explorer, GCP Billing Export, and Azure Cost Management. Correlates anomalous compute spikes to the exact developer resource or un-containerized workload — finding surfaced inline in your IDE before the invoice arrives.
- Per-feature and per-user token spend tracking across OpenAI, Anthropic, and Bedrock
- Token-bleeding prompt pattern detection — flags high-cost, low-signal calls for Batch API offload
- Raw credentials stay inside your VPC; only sanitized billing deltas cross the MCP boundary
SecOps Guardrail MCP
Compiles and lints Terraform state diffs and Kubernetes manifests at plan time — locally, before execution. Flags public S3 bucket policies, OAC misconfiguration, missing NetworkPolicies, and SOC2/HIPAA/CIS violations before any change reaches staging.
- CIS L1/L2, SOC2 Type II, and HIPAA control families evaluated against live state diffs
- Scans manifests for privileged containers, unencrypted secrets, and exposed internal dashboards
- Hard-blocking GitLab CI / GitHub Actions gate — exits non-zero on policy failure
Log-Surfer Observability MCP
Bridges CloudWatch Container Insights and Fluent Bit streams via a scoped, read-only IAM role. Ingests multi-line pod failures, OOMKilled events, and CrashLoopBackOff sequences — redacts PII — and returns structured remediation scripts directly into the developer context window.
- CloudWatch Logs Insights, Fluent Bit HTTP output, and Loki LogQL endpoints all supported
- Auto-redacts email addresses, auth tokens, and IP patterns before LLM context ingestion
- Returns kubectl patch commands and Helm overrides — executable output, not prose
- Local binary, zero network egress
- Single cluster / single provider
- FinOps MCP: 7-day delta, read-only
- SecOps Guardrail: CIS L1 controls only
- Log-Surfer: manual query, no streaming
- Community Slack support
- Multi-cluster, multi-provider (AWS + GCP + Azure)
- Full FinOps MCP: real-time webhooks + per-user token tracking + IDE annotations
- Full SecOps Guardrail: SOC2, HIPAA, CIS L1+L2 live state diff scanning
- Full Log-Surfer: live stream triage + PII redaction pipeline
- Per-developer RBAC audit logs
- 99.9% SLA · 4-hour priority engineering response
Elite Async Intervention. Code Shipped in 72 Hours.
Fixed-scope. No retainers. No bloated SOWs. Supply read-only artifacts asynchronously — receive production-ready Terraform patches and a compliance blueprint within 72 hours. Zero alignment meetings required.
FinOps, LLM Token Cost Management & Audits
Runaway enterprise AI spend is split across two distinct billing surfaces — cloud compute and AI API tokens. We audit both simultaneously: over-provisioned EKS/GKE node groups, broken Karpenter consolidation policies, and idle compute are dissected alongside per-feature token consumption profiles, prompt bloat, and synchronous API call patterns that belong in a batch queue.
A prioritized, line-item remediation map targeting immediate 40–60% run-rate reductions across both compute and AI API billing surfaces. Every finding is CVSS-equivalent severity-ranked, owner-attributed, and linked to a specific remediation PR.
Tailored Karpenter consolidation policies and disruption budget configurations, EKS/GKE cluster right-sizing manifests, Spot Fleet deployment strategy scripts, Reserved Instance gap analysis, and a full ledger of orphaned cloud resources — stale load balancers, unattached EBS volumes, forgotten cross-AZ egress patterns.
- Tiered Model Routing design — SLM vs. flagship LLM routing logic mapped to your actual request complexity distribution
- Server-side Prompt Caching architecture — cache config cutting input token costs by up to 90% on repeated context workloads
- Batch API migration plan — decoupling non-urgent workloads (bulk embeddings, nightly classification) from synchronous API spend
- Token consumption profiling — per-feature, per-user spend breakdown across OpenAI, Anthropic, Bedrock, and Vertex endpoints
Security Gap Analysis & Compliance VAPT
Compliance checkboxes don't stop breaches. We execute a rigorous technical audit against CIS Benchmarks, SOC2 Type II control families, and HIPAA safeguard requirements — followed by active Vulnerability Assessment and Penetration Testing to confirm exploitability, not just theoretical exposure. AI-specific attack surfaces — prompt injection vectors, model exfiltration paths, and LLM endpoint abuse — are enumerated alongside traditional infrastructure.
Exhaustive, CVSS-scored exposure mapping across container runtimes, Kubernetes network boundaries, storage perimeters, and LLM API surfaces. Every finding includes proof-of-concept reproduction steps, blast radius assessment, and a compliance control cross-reference.
IAM hardening manifests with least-privilege IRSA and GKE Workload Identity templates, automated container vulnerability scanning pipeline configurations (Trivy/Grype), network isolation blueprints (OPA NetworkPolicy templates), and secure Origin Access Control (OAC) configurations for S3/GCS storage buckets — all control-mapped to CIS, SOC2, and HIPAA frameworks.
- IAM hardening — least-privilege IRSA and GKE Workload Identity bindings, full over-permissive principal sweep
- Container image scanning with Trivy/Grype across all in-scope registry tags; base image upgrade paths included
- Kubernetes network policy audit — flat namespaces, missing PodSecurityAdmission enforcement, exposed dashboards
- PII and credential redaction architecture — token/email/entity sanitization before data routes to any public LLM endpoint
- Active VAPT — authenticated and unauthenticated enumeration against staging, including LLM endpoint abuse scenarios
Completely Frictionless.
Three steps covering both engagement models. Every action is documented, auditable, and engineered to ship without disrupting your team's sprint cadence.
Ingest
You supply read-only artifacts. Nothing else is required.
Drop read-only IAM role ARNs, anonymized IaC repositories (Terraform/OpenTofu/Helm), log manifests, CloudTrail exports, and LLM token usage reports into our AES-256 encrypted ingestion vault. No screen shares. No calls. No live environment access of any kind.
- Encrypted S3 drop zone — presigned upload URLs expire after 24 hours, artifacts purged on receipt
- Accepts .tfstate files, .yaml manifests, GitHub/GitLab repo archives, raw log bundles, and token usage CSVs
- Read-only IAM scope cryptographically verified before ingestion proceeds — write permissions explicitly rejected at the boundary
Analyze & Deliver
Air-gapped pipeline. Production-ready code output in 72 hours.
Artifacts enter an isolated evaluation sandbox. Proprietary automated scanning scripts execute FinOps analysis, token consumption profiling, CIS Benchmark compliance checks, VAPT enumeration, and IaC linting in parallel — with no human access to your raw data. Within 72 hours, the client receives a private Git repository containing ready-to-ship Terraform patches, CVSS-scored security findings with remediation PRs, and a prioritized optimization blueprint.
- Isolated execution environment — all artifacts purged from sandbox 72 hours post-delivery
- Checkov, Trivy, Semgrep, and proprietary FinOps + token profiling scripts run concurrently
- Private repo delivery via GitHub or GitLab — branched, PR-ready, reviewer-annotated with full rationale
Integrate
Pull a verified repository or connect your IDE directly.
For software purchases: access a private, modular code repository with signed release tags, Terraform modules, and Helm charts — mergeable into any monorepo with no undocumented dependencies. For MCP server subscriptions: configure your IDE or agent framework with the provided endpoint and API key — credentials never leave your environment.
- Signed git tags with build attestation — every software release is reproducibly buildable from source
- MCP server config snippet generated at checkout — single-line paste into Claude Code or Cursor MCP settings
- Token Sentinel Gateway: update your LLM client base URL — zero other application code changes required
Start Your Infrastructure & AI Ops Audit
Drop your read-only artifacts. Receive production-ready Terraform patches, a CVSS-scored security report, and an optimization blueprint — within 72 hours. Zero meetings.
- 30-min async audit scoping — stack, scope, and drop zone confirmation
- Google Meet link auto-generated & sent instantly
- Verified email confirmation + calendar invite
- Zero-commitment — cancel or reschedule anytime
After confirming your email you'll pick a 30-min slot for artifact drop zone setup. A Google Meet link is included in your confirmation — no pre-call prep required.
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