Prototype reliability
Agent loops, brittle retrieval, non-deterministic tool calls, weak structured outputs, and missing failure recovery.
Production Agentic AI Engineering
Build, secure, and operate AI agents that are ready for production.
DeepVention engineers agent integrations, multi-agent orchestration, secure MCP infrastructure, evaluations, guardrails, and AgentOps for regulated SaaS, healthtech, fintech, and enterprise AI teams.
AI Agent Integration
Multi-Agent Orchestration
Secure MCP Infrastructure
AgentOps & Evaluation
AI Security & Guardrails
Where prototypes break
AI demos are easy. Production systems are not.
The hard engineering starts when agents meet real users, enterprise systems, permissions, sensitive data, and production reliability requirements.
Enterprise integration
Identity, APIs, internal data, permissions, tenant boundaries, and secure access to business systems.
Observability & evaluation
Missing traces, weak test datasets, no regression gates, and unclear cost, latency, or agent quality.
Security & governance
Prompt injection, sensitive-data exposure, over-permissioned tools, weak auditability, and missing human controls.
Flagship services
Production AI engineering for systems that have to work beyond the demo.
We help software and AI teams integrate, orchestrate, secure, evaluate, and operate agentic systems in production.
Production AI Agent Integration
Connect agents to your product, knowledge, APIs, and operational systems with controlled tool access, retrieval, structured outputs, evaluations, and telemetry.
ProductionEngineering
Multi-Agent Systems & Orchestration
Design supervisor, routing, handoff, state, approval, retry, and failure-recovery patterns for workflows that need more than one reasoning component.
ProductionEngineering
Secure MCP Infrastructure
Build MCP servers and gateway layers with identity, authorization, tenant isolation, tool allowlists, rate limits, secrets handling, and audit logs.
ProductionEngineering
AgentOps, Evals & Observability
Trace agent behavior, measure quality, cost, latency, tool failures, and release regressions so production decisions are based on evidence.
ProductionEngineering
AI Security, Guardrails & Governance
Implement prompt-injection defenses, validation, redaction, tool authorization, human approval, policy controls, auditability, and kill switches.
ProductionEngineering
AI Workflow Automation
Engineer AI-assisted workflows around APIs, documents, CRM/ERP systems, approvals, schedules, and event-driven operations.
ProductionEngineeringHow we engage
From architecture review to production operation.
A structured engineering path for teams that need confidence before scaling autonomous behavior.
01
Architecture Discovery
Map the workflow, data, integrations, permissions, failure modes, and production constraints.
02
Proof of Value
Validate the highest-risk technical assumptions with a focused implementation and measurable acceptance criteria.
03
Production Engineering
Build the runtime, integrations, state, tool boundaries, deployment, and operator experience.
04
Evals & Security Review
Add regression datasets, traces, policy checks, adversarial cases, approval gates, and release criteria.
05
Managed AgentOps
Operate and improve the system through telemetry, evaluations, incident learning, and controlled releases.
Where we fit
For software teams with real integration, reliability, and governance constraints.
Regulated B2B SaaS
Agentic features that must respect tenant boundaries, permissions, auditability, and existing product architecture.
Healthtech
AI workflows designed around sensitive data, human oversight, traceability, and security-conscious integration.
Fintech / Insurtech
Tool-using agents and workflows with strict authorization, review points, logging, and controlled system access.
Enterprise AI Platforms
Shared agent infrastructure, gateways, evaluations, observability, and reusable tool interfaces across teams.
AI-native SaaS
Production hardening for products where agents, retrieval, and tool use are part of the core user experience.
Engineering capabilities
Framework-aware. Architecture-first.
We select tools around system requirements rather than forcing every project into one agent framework.
Agent orchestration
LangGraph, OpenAI Agents SDK, CrewAI, AutoGen, structured tool calling, state machines, approval flows.
Backend & infrastructure
Python, FastAPI, TypeScript, Node.js, PostgreSQL, Redis, Docker, Kubernetes, AWS, Azure, GCP.
Security & observability
OAuth/OIDC, authorization policies, API gateways, OpenTelemetry, LangSmith, Langfuse, Traceloop, customer-approved stacks.
AI agents & intelligent applications
Software built to think, act, and automate.
Explore illustrative product surfaces shaped around agents, integrations, retrieval, workflow automation, and the controls required for reliable operation.
Portfolio system
Secure Agent Gateway for a B2B SaaS Platform
A reference architecture for a secure agent gateway with allowlisted tools, approval checkpoints, traces, and regression datasets.
Professional engineering notes
Practical thinking for AI systems that do real work.
We publish technical notes on AI agents, agentic applications, workflow automation, RAG, product engineering, evaluation, and production operations.
Engineering Notes
Vibe Code Rescue: How to Turn an AI-Built Prototype into Production-Ready Software
AI coding tools can turn an idea into a working demo quickly. Here is a practical code audit and refactoring path for making that…
Aug 26, 2026
Agentic AI Architecture
How to Scale an AI-Native Web Application Beyond the Prototype
Scaling an AI-native application is a product and systems problem, not simply a larger server. This guide covers data design, APIs, background work, caching,…
Aug 26, 2026
RAG & Knowledge Systems
Production-Grade AI Agents: RAG, Tool Calling, and Human Approval
A production AI agent needs more than a capable model. It needs permission-aware retrieval, explicit tools, bounded autonomy, and a human approval path for…
Aug 26, 2026
Careers
Build production AI systems that have to work in the real world.
Open role · Local demo
Demo – Senior AI Platform Engineer
Engineering · Local demo – replace before launch
Help design agent runtimes, secure tool infrastructure, evaluation loops, and observability for production-minded AI systems.
Replace before launch
Planning an agentic system that has to survive production?
Talk through your architecture, integration constraints, security boundaries, evaluation strategy, or reliability problems with DeepVention.