Enterprise AI Engineering

We Build AI Systems That
Actually Work.

Biz Craft Global designs and delivers production-grade AI infrastructure — from intelligent RAG pipelines and multi-agent platforms to secure, self-hosted deployments for regulated industries.

6
Core Service Areas
27+
Technologies Mastered
100%
Production-Grade Delivery
LangGraph
Pinecone
Kubernetes
DeepEval
LangGraph
RAG Systems
Multi-Agent Orchestration
Model Context Protocol
LLM Fine-Tuning
Pydantic v2
Pinecone
Guardrails AI
DeepEval
LangSmith
Neo4J Graphiti
PostgreSQL RLS
Kubernetes
DSPy
LangGraph
RAG Systems
Multi-Agent Orchestration
Model Context Protocol
LLM Fine-Tuning
Pydantic v2
Pinecone
Guardrails AI
DeepEval
LangSmith
Neo4J Graphiti
PostgreSQL RLS
Kubernetes
DSPy
Who We Are

Deep Technical Expertise.
Practical Delivery.

Biz Craft Global is an AI engineering consultancy specialising in the design and delivery of production-grade AI systems. We combine deep expertise in the latest frameworks, security-first architecture, and hands-on implementation to build AI that performs reliably in the real world.

We work with organisations across finance, legal, healthcare, and enterprise operations — building systems that are intelligent, secure, and built to last.

01

Framework Depth

We work at the frontier of the AI ecosystem — from LangGraph and DSPy to MCP and Guardrails — not just wrapping APIs but engineering real systems.

02

Security by Design

Every system we build treats security as a structural property — not an afterthought. Data isolation, access control, and compliance readiness are built in from day one.

03

Production Mindset

We deliver code that runs in production — with evaluation pipelines, observability, latency benchmarks, and regression tests included as standard.

04

Vendor Independence

We architect for your operational freedom — self-hosted, BYOD, and air-gapped deployment options mean you stay in control of your data and infrastructure.

What We Do

Six Areas of
Deep Expertise

End-to-end AI engineering services — from knowledge retrieval architecture and multi-agent orchestration to model optimisation and secure enterprise deployment.

01

Advanced RAG Systems

We design and implement retrieval-augmented generation architectures that give your AI accurate, context-aware access to your organisation's knowledge — at scale, with speed.

Standard RAGGraph RAGHybrid RetrievalDense + Sparse SearchDocument ParsingUnstructured Data Ingestion
02

MCP & Multi-Agent Orchestration

We build intelligent, collaborative AI systems that go beyond single-model interactions — designing coordinated agent workflows, tool integrations, and autonomous decision pipelines.

Model Context ProtocolOpen-Source MCPSelf-Hosted MCPLangGraphAgent Task DelegationAutonomous Pipelines
03

Latest AI Frameworks & Tooling

We stay at the forefront of the AI ecosystem — integrating the most current and widely adopted frameworks and tools to build powerful, maintainable LLM-powered applications.

LangChainLangGraphInstructorDSPyPydantic v2API Integration
04

Model & System Evaluation

Ensuring AI systems perform reliably and safely is central to our engineering practice. We deliver structured evaluation, tracing, benchmarking, and quality assurance as a built-in deliverable.

DeepEvalLangSmithRetrieval AccuracyLatency BenchmarkingRegression TestingQA Pipelines
05

Secure & Self-Hosted AI

We architect AI systems with security, privacy, and operational independence as first-class requirements — building fully self-hosted, on-premise, and private-cloud deployments for regulated industries.

Self-Hosted DeploymentsAir-Gapped SystemsData ResidencyAccess ControlPostgreSQL RLSZero Vendor Lock-In
06

LLM Fine-Tuning & Optimisation

We help organisations get the most from their AI investments through targeted model customisation, domain-specific fine-tuning, and systematic prompt and context engineering.

Domain Fine-TuningPrompt EngineeringContext EngineeringSkill OptimisationDSPy PipelinesAccuracy Tuning
Technology Stack

Tools We Master,
Not Just Use

27 carefully selected technologies across six layers — each chosen for production reliability, security depth, and architectural fit. We work with these daily.

Claude / Anthropic Models
AI & Orchestration
Primary LLMs for reasoning, generation, and structured output extraction.
Core cognitive engine across multi-agent and RAG systems.
LangGraph
AI & Orchestration
Stateful, graph-based multi-agent orchestration and workflow framework.
Complex agent execution graphs with human-in-the-loop controls.
LangChain
AI & Orchestration
Framework for building LLM-powered chains and application pipelines.
Rapid LLM application integration and tool-chain construction.
DSPy
AI & Orchestration
Programmatic prompt optimisation and automated refinement framework.
Automated system prompt optimisation and tool-use pattern tuning.
Instructor
AI & Orchestration
Structured output extraction enforced from LLM API responses.
Strict JSON schema enforcement at the API boundary.
Pydantic v2
Validation & Safety
Python data validation with strict type enforcement and fast parsing.
Schema validation layer — catches malformed outputs in under 10ms.
Guardrails AI
Validation & Safety
Policy-based LLM output validation and correction framework.
Deterministic rule enforcement — financial limits, domain allow-lists, CRM safeguards.
NeMo Guardrails
Validation & Safety
NVIDIA conversational AI safety and non-probabilistic policy rails.
Operational policy enforcement at the agent execution layer.
PostgreSQL + RLS
Memory & Storage
Relational database with native Row-Level Security for multi-tenant isolation.
Persistent memory, audit logs, and GDPR-compliant data storage.
Redis
Memory & Storage
In-memory cache, pub/sub broker, and rate-limit counter store.
Working memory scratchpad and API rate management.
Pinecone
Memory & Storage
Serverless vector database with namespace-level tenant isolation.
Semantic memory and RAG retrieval with physical data separation.
Neo4J / Graphiti
Memory & Storage
Temporal knowledge graph tracking entities and relationships over time.
Graph-based RAG and long-term contextual intelligence.
Weaviate / Qdrant
Memory & Storage
Self-hostable open-source vector database alternatives.
BYOD and air-gapped vector search deployments.
Amazon S3
Memory & Storage
Scalable object storage with path-based access control.
Document storage with short-lived pre-signed URL access patterns.
PgBouncer
Memory & Storage
PostgreSQL connection pooler for efficient multi-tenant DB connections.
BYOD deployment — safe pooled connections per tenant.
Model Context Protocol (MCP)
Integrations & MCP
Open standard for secure, scoped agent-to-tool communication.
Decouples integration logic from agent code; minimises blast radius.
Salesforce / HubSpot / Pipedrive
Integrations & MCP
Enterprise CRM platforms with structured contact and deal data.
Scoped CRM read/write access — admin privileges denied by default.
Google Drive / Notion / Slack
Integrations & MCP
Productivity and collaboration suites.
Per-file OAuth scopes — no global workspace token exposure.
GitHub / Jira
Integrations & MCP
Code hosting and issue tracking platforms.
PR metadata and issue access — repository admin locked out.
QuickBooks / Xero / DocuSign
Integrations & MCP
Accounting and e-signature platforms.
Bounded to safe predefined functions via custom MCP wrappers.
AWS (EKS / Secrets Manager)
Infrastructure
Cloud infrastructure, container orchestration, and encrypted secrets storage.
Managed SaaS hosting and tenant credential management.
Kubernetes + Helm
Infrastructure
Container orchestration with package-managed deployment charts.
Air-gapped and on-premise deployments via custom Helm bundles.
Docker Compose
Infrastructure
Multi-container orchestration for local and self-hosted deployments.
Bundled self-hosted deployment for enterprise on-premise environments.
JWT Authentication
Infrastructure
JSON Web Token standard for stateless, verifiable session management.
Cross-tenant routing validation and secure session enforcement.
LangSmith
Evaluation & Observability
End-to-end LLM tracing, debugging, and evaluation platform.
Pipeline observability, trace inspection, and regression benchmarking.
DeepEval
Evaluation & Observability
Structured LLM and RAG evaluation framework with metric coverage.
Retrieval accuracy, answer quality, and hallucination measurement.
Langfuse
Evaluation & Observability
Open-source LLM observability with per-project isolation.
Tenant-isolated tracing; tool call latency and audit logging.
Our Process

How We Deliver

A structured four-phase process that takes every engagement from discovery to a production system you can operate with confidence.

01
Phase One

Discovery & Architecture

We map your data, workflows, compliance requirements, and integration landscape — then design a system architecture tailored to your constraints and objectives.

02
Phase Two

Build & Integration

We implement the full stack — RAG pipelines, agent orchestration, tool integrations, memory layers, and validation middleware — using the frameworks best suited to your needs.

03
Phase Three

Evaluation & Hardening

Every system is evaluated against structured benchmarks for retrieval accuracy, output quality, latency, and security before it goes anywhere near production.

04
Phase Four

Deployment & Optimisation

We deploy to your chosen infrastructure tier — SaaS, BYOD, or air-gapped Kubernetes — and run ongoing optimisation cycles to keep the system performing as your data evolves.

Why Biz Craft Global

Engineering Discipline
Meets AI Depth

We are not a prompt shop. We build production AI systems with the rigour of software engineering and the depth of AI research.

Framework Mastery

We Work at the Frontier

We don't just wrap OpenAI APIs. We implement full LangGraph execution graphs, build custom MCP servers, engineer DSPy optimisation pipelines, and work directly with the underlying models — fine-tuning, evaluating, and hardening them for your specific domain.

Security Engineering

Security Is Structural, Not Cosmetic

We implement PostgreSQL Row-Level Security, physical vector namespace isolation, MCP scope restrictions, and multi-layer output validation — not as add-ons but as core architectural decisions. Systems we build meet the requirements of finance, legal, and healthcare from day one.

Evaluation First

Every System Gets Evaluated

We ship evaluation pipelines alongside your AI system — not as an afterthought. Using DeepEval, LangSmith, and Langfuse, we give you systematic visibility into retrieval accuracy, answer quality, latency, and regression over time.

Deployment Flexibility

Your Data Stays Where You Need It

We design for operational independence. Whether you need fully managed SaaS, a BYOD hybrid model connecting to your own databases, or a completely air-gapped Kubernetes deployment — we architect and deliver all three, with no vendor lock-in by design.

Deployment Models

We Deploy Where
You Need Us To

Three distinct infrastructure deployment approaches — designed to accommodate the compliance, privacy, and operational requirements of any organisation.

Option 01 · Managed

Fully Managed SaaS

We host and operate your AI system on production-hardened cloud infrastructure with multi-tenant data isolation enforced at every layer.

  • Production-hardened cloud infrastructure
  • Multi-tenant data isolation across all layers
  • Automated backups and data export pipelines
  • Built-in compliance and audit tooling
  • Ideal for fast-moving teams without infrastructure overhead
Option 02 · Hybrid

Bring Your Own Data (BYOD)

Our application and agent layers connect transparently to your infrastructure. You own and control all your databases, vector stores, and files.

  • Compatible with PostgreSQL, Pinecone, Weaviate, Qdrant
  • Encrypted connection routing via your Secrets Manager
  • Connection pooling with PgBouncer
  • JWT-validated cross-tenant routing safety
  • Ideal for organisations with existing cloud infrastructure
Option 03 · Self-Hosted

Air-Gapped / On-Premise

The complete AI system runs within your corporate perimeter — deployed via Helm charts and Docker Compose bundles with no external network egress required.

  • Kubernetes deployment with custom Helm charts
  • Self-hosted vector search (Qdrant) and observability (Langfuse)
  • Customer-managed LLM inference gateways
  • Local licensing with offline resilience built in
  • Ideal for regulated industries: finance, legal, healthcare, defence
Start a Conversation

Ready to Build Something That Lasts?

Whether you need a single RAG pipeline or an end-to-end multi-agent platform, we bring the engineering depth to get it right the first time.

Schedule a Technical CallDownload Capabilities Brief