< 180msTool Call Latency
Deterministic function calling with strict JSON schema parsing and sub-200ms round-trip tool execution.
SabrixaApplied AI & Systems Practice
Autonomous Systems. Sovereign Intelligence. Engineered for Production.
Sabrixa designs, benchmarks, and deploys enterprise-grade autonomous agent systems, deterministic RAG pipelines, and self-hosted private LLMs for venture-backed founders and scaling commercial operators.
OPERATIONAL EXCELLENCE
Engineering Guarantees Backed by Rigorous SLAs
Every AI system we deploy is measured against strict mathematical accuracy, token efficiency, and sub-200ms latency boundaries.
99.4%Retrieval Grounding
Contextual RAG with hybrid lexical-dense re-ranking, eliminating hallucinations from enterprise search.
100%Data Sovereignty
Zero-retention VPC isolation, private on-premises LLM inference, and full ownership of fine-tuned weights.
Senior OnlyPrincipal AI Engineers
Direct execution by systems and machine learning engineers. No junior trainees or non-technical account reps.
APPLIED AI RESEARCH & DELIVERY
Inside the Sabrixa Applied AI Lab
Where multi-step state machines are stress-tested, RAG vector embeddings are clustered, and private GPU inference servers are hardened.
Sabrixa
Claude 3.5 SonnetLangGraph v0.2Qdrant Vector DBvLLM InferenceNeMo Guardrails
SabrixaDeterministic State Graphs & Low-Latency Retrieval
Every AI workflow is benchmarked for sub-200ms latency, zero memory leaks, and mathematical grounding before production VPC sign-off.
ENGINEERING DISCIPLINES
Applied AI Practices Built for Enterprise Reliability
We do not build toy demo wrappers. We engineer high-throughput, fault-tolerant AI systems designed to operate under strict enterprise compliance and latency requirements.
SabrixaPractice 01
< 180msTool Latency
Autonomous Agent Systems & Multi-Step Workflows
We engineer resilient state machine agents capable of multi-step tool execution, structured JSON schema validation, and human-in-the-loop exception routing without infinite loops or unbounded token costs.
Production Deliverables
- ✓Cyclic state graph orchestration with deterministic rollback and fault recovery.
- ✓Strict Pydantic JSON schema output enforcement with automatic retry loops.
- ✓Asynchronous parallel tool dispatch with sub-180ms execution latency SLAs.
- ✓Human-in-the-loop approval gates for high-stakes operational actions.
◆Principal Architect Note
“We reject brittle single-prompt chains. Every enterprise agent is engineered as a deterministic state machine with verifiable termination criteria.”
SabrixaPractice 02
99.4%Grounding Precision
Enterprise Document Intelligence & Semantic Vector Search
High-precision Retrieval-Augmented Generation (RAG) for complex financial filings, legal contracts, and proprietary internal knowledge. We implement contextual chunking, ColBERT late-interaction scoring, and hallucination-free answer grounding.
Production Deliverables
- ✓Semantic layout-aware PDF and document parsing with contextual chunking.
- ✓Hybrid retrieval fusing BM25 lexical keyword search with dense vector indexing.
- ✓Late-interaction re-ranking for ultra-high precision query-passage matching.
- ✓Continuous automated eval pipelines measuring faithfulness and context relevance.
◆Principal Architect Note
“Retrieval failure is the primary cause of hallucination. We guarantee citation-backed responses strictly anchored to verified enterprise source data.”
SabrixaPractice 03
100%VPC Data Isolation
Self-Hosted On-Premises LLMs & Private Inference
Air-gapped and VPC-isolated open-weight LLMs optimized with vLLM, TensorRT-LLM, and FP8/INT4 quantization. Complete data sovereignty compliant with DPDP Act 2023, HIPAA, and GDPR zero-data-retention mandates.
Production Deliverables
- ✓High-throughput inference deployment on dedicated NVIDIA H100/A100 GPU clusters.
- ✓Domain fine-tuning (LoRA / QLoRA) for proprietary taxonomy, tone, and compliance.
- ✓End-to-end zero-egress VPC topology with zero third-party telemetry or cloud leaks.
- ✓Dynamic batching and PagedAttention optimization achieving 3x throughput gains.
◆Principal Architect Note
“You retain 100% intellectual property, model weights, and data sovereignty. Zero third-party API dependencies, zero vendor lock-in.”
SabrixaPractice 04
< 450msEnd-to-End Voice Turn
Low-Latency Real-Time Audio & Conversational Voice AI
Sub-500ms bidirectional voice systems and multimodal vision engines built on WebSockets, OpenAI Realtime API, Whisper Large v3, and Cartesia Sonic for conversational call handling and live screen intelligence.
Production Deliverables
- ✓Sub-500ms conversational turn-taking with natural speech interruption and barge-in.
- ✓Full-duplex audio streaming over resilient WebSockets with zero audio jitter.
- ✓Real-time multimodal vision pipelines for automated screen and document inspection.
- ✓Function calling during active voice streams for live CRM and database lookups.
◆Principal Architect Note
“Conversational voice must feel instant to human ears. We optimize every millisecond between acoustic arrival, inference, and synthetic speech streaming.”
PRODUCTION INFRASTRUCTURE
The Enterprise AI Technology Stack
Battle-tested frameworks, state-of-the-art vector engines, and private GPU serving infrastructure with zero experimental bloat.
Frontier & Open-Weight LLMs
Rigorous model selection balancing intelligence, latency, token costs, and data privacy boundaries.
Anthropic Claude 3.5 SonnetOpenAI GPT-4o & GPT-4o-miniMeta Llama 3.3 70BDeepSeek-V3 / DeepSeek-R1Mistral Large 2Qwen 2.5 72B
Deterministic State Machines
Structured workflows, tool calling, cyclic state graphs, and reliable schema parsing.
LangGraph v0.2DSPy Program SynthesisLlamaIndex WorkflowsPydantic v2 ValidationTemporal OrchestrationFastAPI Async Endpoints
High-Throughput Vector DBs
Sub-millisecond semantic search, hybrid sparse-dense indexing, and late-interaction re-ranking.
Qdrant Vector DatabasePostgreSQL + pgvectorColBERT v2 Late InteractionCohere Re-Rank 3BGE-M3 Multilingual EmbeddingsUnstructured.io Parsing
High-Performance Serving
Dedicated GPU deployment engines with PagedAttention, INT4/FP8 quantization, and continuous batching.
vLLM EngineTensorRT-LLM (NVIDIA)Ollama EnterpriseHugging Face TGIONNX RuntimeAWS Bedrock / Azure AI VPC
Enterprise Defense & Evals
Hallucination controls, prompt injection shields, PII redaction, and programmatic regression testing.
NVIDIA NeMo GuardrailsGuardrails AIPromptfoo CI TestingRagas Grounding EvalsPresidio PII RedactionLangSmith Evals
Trace & Token Monitoring
Deep span-level tracing, latency profiling, cost attribution, and production error triage.
Langfuse Open-Source TracingArize Phoenix ObservabilityOpenTelemetry CollectorDatadog LLM ObservabilityPrometheus & Grafana DashboardsCustom Audit Logs
THE SABRIXA DOCTRINE
Engineered Systems vs Agency AI Wrappers
Why venture founders and enterprise CTOs trust Sabrixa over generic digital agencies and no-code wrapper creators.
| Architectural Dimension | The Sabrixa Sovereign Protocol | Generic Agency AI Wrappers |
|---|---|---|
| Architectural Foundation | ✓Deterministic cyclic state machines (LangGraph) with strict schema validation and graceful fallback paths. | ✕Naive single-prompt chains or brittle no-code wrapper tools prone to catastrophic loop failures. |
| RAG & Hallucination Elimination | ✓Hybrid dense-lexical retrieval (ColBERT + Qdrant) with metadata filtering and citation grounding verification. | ✕Basic cosine distance on arbitrary document chunks with zero validation, leading to severe hallucination. |
| Data Sovereignty & Privacy | ✓Zero-retention VPC isolation or self-hosted private LLMs (vLLM / TensorRT). Full compliance with DPDP & GDPR. | ✕Direct calls to third-party public APIs with unclear data logging policies and privacy exposure. |
| Latency & Engineering SLAs | ✓Sub-180ms tool executions, streaming WebSockets, and PagedAttention optimizations with strict uptime SLAs. | ✕Unoptimized multi-second blocking calls with no streaming, yielding terrible user experience. |
| Code & Weights Ownership | ✓100% intellectual property, clean Git repository handover, model weights, and fine-tuning datasets are yours. | ✕Proprietary platform lock-in, recurring monthly markups, and zero exportable code or assets. |
| Execution Team | ✓Senior Machine Learning and Systems Engineers directly architecting and executing every sprint. | ✕Junior developers copying boilerplate tutorial scripts supervised by non-technical project managers. |
DELIVERY PROTOCOL
4-Phase Applied AI Sprint Methodology
A disciplined, milestone-driven execution cycle taking you from feasibility blueprint to hardened production VPC deployment in 30 days.
Architecture Blueprint & Feasibility Audit
We audit your data assets, define strict latency & accuracy SLAs, select optimal model topologies (frontier vs open-weight), and establish deterministic state graphs.
Key Output: Unambiguous architectural specification, data contract lock, and milestone schedule.
Core Staging Slice & Guardrail Pipeline
We deploy working vector indexing pipelines, LangGraph state machines, and structured tool calling directly on a live staging environment for early stakeholder validation.
Key Output: Live staging URL with interactive tool execution and ground-truth evaluation suites.
Latency Optimization & Stress Hardening
We tune chunking strategies, optimize inference throughput via vLLM/TensorRT, benchmark under concurrent load, and configure NeMo Guardrails against adversarial prompts.
Key Output: Sub-200ms tool latency verified, 99%+ grounding precision, zero memory leaks.
VPC Deployment & Sovereign IP Handover
We deploy to your private AWS/GCP VPC or on-premises GPU infrastructure, execute final security penetration tests, and conduct comprehensive engineering handover.
Key Output: Full GitHub repository ownership, CI/CD pipelines, documentation, and zero lock-in.
ENGAGEMENT MODELS
Transparent Commercial Partnership Tiers
Direct access to senior AI systems engineers with fixed-price sprint commitments and complete IP ownership.
48-Hour AI Systems & Security Audit
A surgical architectural and security review of your existing AI pipelines, RAG retrieval quality, latency bottlenecks, and token cost economics.
Ideal For: Startups and enterprises experiencing high hallucination rates, slow tool latency, or spiraling LLM API bills.
Key Inclusions
- ✓End-to-end audit of RAG chunking and vector index precision.
- ✓Latency profiling across model calls, tool executions, and streaming.
- ✓Token economics analysis with actionable 40–70% cost reduction map.
- ✓Adversarial prompt injection & data leakage vulnerability report.
- ✓Actionable 30-day technical remediation blueprint.
Timeline: Delivered within 48 Business Hours
Schedule 48-Hour AuditMost Popular
PRODUCTION SPRINTFixed-Scope Applied AI Sprint
A 2 to 4-week dedicated engineering sprint delivering production-grade AI agent systems, high-precision RAG engines, or private on-premise LLMs.
Ideal For: Founders and technical leaders requiring enterprise-grade AI capabilities deployed to production with fixed pricing and guaranteed SLAs.
Key Inclusions
- ✓Custom LangGraph multi-step autonomous agent state machines.
- ✓High-precision Qdrant/pgvector RAG with ColBERT re-ranking.
- ✓vLLM/TensorRT private model deployment in your VPC.
- ✓Full NeMo Guardrails safety & automated Ragas eval suite.
- ✓100% intellectual property, clean Git repository, and handover docs.
Timeline: 14–28 Business Days to Production
Book Engineering SprintDedicated AI Systems Advisory
Continuous fractional AI systems architecture and senior machine learning engineering partnership for scaling technology companies.
Ideal For: Organizations deploying multiple AI capabilities who require ongoing architectural oversight, model fine-tuning, and performance optimization.
Key Inclusions
- ✓Dedicated senior AI systems architect embedded in your sprints.
- ✓Continuous evaluation, benchmark monitoring, and model upgrades.
- ✓Custom LoRA/QLoRA domain fine-tuning and dataset curation.
- ✓Priority 4-hour SLA on critical production AI incidents.
- ✓Regular architecture reviews and quarterly AI roadmap planning.
Timeline: Monthly Engineering Retainer (Quarterly Alignment)
Inquire for RetainerDATA PRIVACY & LEGAL SOVEREIGNTY
Request Security WhitepaperZero-Data-Retention & Air-Gapped VPC Compliance
Every Sabrixa model deployment complies with zero-data-retention agreements, enterprise VPC boundaries, and local regulatory laws including India DPDP Act 2023, EU GDPR, and US HIPAA. Your data is never used for model training.
TECHNICAL CLARITY
Frequently Asked Architectural Questions
Direct, technical answers to common questions asked by CTOs, technical founders, and enterprise engineering leads.
How does Sabrixa eliminate hallucinations in production AI systems?
We replace naive prompt engineering with a multi-layered deterministic architecture: (1) Layout-aware document parsing with contextual chunking, (2) Hybrid lexical BM25 and dense vector retrieval with ColBERT late-interaction re-ranking, (3) Citation-grounded prompt constraints that forbid ungrounded assumptions, and (4) Programmatic post-generation validation using NeMo Guardrails and Pydantic schema verifiers before any output reaches users.
Can you deploy AI models entirely within our private AWS, Azure, or GCP VPC?
Yes. Data sovereignty is a core pillar of our practice. We specialize in deploying open-weight models (Meta Llama 3.3 70B, DeepSeek-V3/R1, Mistral Large 2) using vLLM and TensorRT-LLM inside your private cloud VPC or on-premises GPU servers. Zero data leaves your firewall, and no third-party APIs receive your sensitive customer records.
What GPU infrastructure is required to self-host high-throughput LLMs?
For 70B parameter models (such as Llama 3.3 70B or Qwen 2.5 72B), we recommend 2x to 4x NVIDIA A100 (80GB) or H100 GPUs using FP8/INT4 quantization with vLLM PagedAttention, easily serving 50+ concurrent requests. For smaller 8B–14B models, a single NVIDIA L4 or RTX 4090 GPU provides exceptional sub-100ms time-to-first-token performance at minimal operational cost.
How do you ensure compliance with data protection laws (DPDP Act 2023, GDPR, HIPAA)?
We implement strict zero-data-retention agreements for frontier API endpoints (Anthropic & OpenAI enterprise tiers) and complete zero-egress networking for private VPC deployments. Automated PII detection and redaction pipelines (Microsoft Presidio) sanitize inputs before inference, and all data at rest and in transit is encrypted using AES-256 and TLS 1.3.
Do we own all intellectual property, fine-tuned weights, and source code?
100% yes. From Day 1, all code is committed directly to your private GitHub/GitLab repositories. All custom fine-tuned weights (LoRA adapters), vector embeddings, database schemas, and orchestration pipelines belong exclusively to your company under standard IP assignment terms. We never implement proprietary vendor lock-in.
How do you transition and onboard our in-house engineering team?
Every project concludes with comprehensive architectural documentation, recorded code walkthroughs, automated test suites (Promptfoo & Pytest), and hands-on pair-programming sessions with your engineers. We build software designed to be maintainable by any senior TypeScript or Python engineer without ongoing agency dependence.
GET STARTED
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Skip the experimental demo prototypes. Partner with senior ML and systems engineers to build deterministic, high-throughput AI infrastructure tailored to your enterprise.