Venzpire
Apply for a call
Services Work Pricing About Blog FAQ

AI agents that do the work, safely

We design and build AI agents that read, research, decide and take action across your CRM, inbox, documents and internal tools, with clear limits, human approval where it matters and a full log of everything they do.

Apply for a strategy call Message on WhatsApp
The short answer

Venzpire builds custom AI agents in 6–12 weeks, starting from $15,000. We use LangGraph, CrewAI or the OpenAI Agents SDK with GPT, Claude or Gemini, connect the agent to your tools through secure APIs, and add evaluations, guardrails, human-in-the-loop approval and monitoring before it touches real customers or data.

What you get

An agent you can trust in production: it knows what it may do, asks before it does anything risky, and leaves a trail you can audit.

Led by Venktesh RBuilt with Nithin and Deepak, the same senior team from first call to launch.

Investment
From $15,000, fixed quote after discovery
Timeline
6–12 weeks
Best for
Teams automating multi-step work
You own
All code, IP and cloud accounts from day one
After launch
30 days of support included
Apply for a strategy call How we price
  • Workflow mappingWe map the job the agent replaces step by step, decide which steps the model handles and which stay as plain code, and agree success measures.
  • Agent architectureSingle or multi-agent design on LangGraph, CrewAI or the OpenAI Agents SDK, with memory, planning and tool use sized to the task.
  • Tool integrationsSecure connections to your CRM, helpdesk, email, calendars, databases, ERP or any REST API, with least-privilege credentials.
  • Guardrails and approvalsSpending and action limits, input and output checks, and human approval steps for anything irreversible.
  • Evaluation suiteA test set of real scenarios the agent must pass before each release, so changes to prompts or models never silently break it.
  • Monitoring and cost controlTraces of every run, alerts on failures and cost per task, plus model routing to keep unit economics healthy.

Agents clients ask us for

  • Sales and RFP agents that draft answers from your approved knowledge base.
  • Support agents that resolve tickets end-to-end and hand off to humans with full context.
  • Research agents that gather, compare and summarise information into a ready report.
  • Operations agents that process documents, update records and chase missing information.
  • Personal assistant agents that plan tasks, track dependencies and remind at the right moment.

What it costs

Typical Venzpire price ranges. Every project starts with a $1,500 discovery sprint that ends in a fixed quote; the sprint fee is credited to the build.

ScopeTypical investmentTimeline
Discovery sprint: workflow map, prototype agent, fixed quote$1,500 fixed1–2 weeks
Single-workflow agent with 2–3 tool integrations$15,000 – $30,0006–8 weeks
Customer-facing agent with CRM, knowledge base and approvals$30,000 – $60,0008–12 weeks
Multi-agent system across several departmentsFrom $60,00012+ weeks

AI model usage and hosting are billed to your own accounts at cost. How we price

How the project runs

  1. Week 1–2 · $1,500 fixed

    Discovery sprint

    Users, data, model choice and cost per user, pressure-tested. You keep the prototype, architecture and fixed quote.

  2. Weeks 3–10

    Design & build

    A staging link in week one, a live demo every week and a short written update every day.

  3. Before launch

    Evaluate & harden

    Tested on real examples, with guardrails, cost limits and a security review.

  4. Launch & after

    Ship & improve

    Deployed to your cloud and the app stores, with 30 days of support included.

Related work

ReplyMagik — AI RFP response automation screenshot

ReplyMagik — AI RFP response automation

A platform that turns a company's previously approved RFP and security-questionnaire answers into a private knowledge base, then drafts new answers in the company's own voice.

The brief
Sales and security teams were rewriting the same RFP and questionnaire answers for every new deal, with no single source of approved wording.
What we built
Each customer account keeps its own isolated knowledge base, built with OpenAI embeddings, LangChain and a Chroma vector store, and uploads are validated before the AI learns from them. Admin and super admin panels manage knowledge and accounts, and every account gets an API key to generate answers from the tools teams already use. Built on AWS with exports to CSV, Excel and PDF.
  • B2B SaaS
  • OpenAI + RAG
  • Account-isolated knowledge
  • API access
  • AWS

Read the ReplyMagik case study

Korvai — a video editor driven by your own Claude Code illustration

Korvai — a video editor driven by your own Claude Code

Our own native macOS video editor with a real multi-track timeline and a built-in bridge that lets your own Claude Code make and revise edits from a chat.

Why we built it
On-brand video edits usually mean either doing everything by hand or losing control to a fully automated tool; Korvai keeps a real timeline editable by hand while an agent can also drive it directly.
What we built
A Swift app with a Metal compositor, a multi-track timeline (trim, split, ripple delete, crossfades) and brand kits for logos, colors, fonts, music and captions. Claude Code reads and edits the timeline through a built-in MCP tool server, with one undo step per agent turn and approval for anything outside its tools. Transcription runs on device for captions and silence removal.
  • macOS (Swift)
  • Claude Code bridge
  • MCP tool server
  • Metal compositor
  • On-device transcription

Read the Korvai case study

Questions about AI agent development

What is an AI agent, and how is it different from a chatbot?

A chatbot answers questions. An AI agent completes tasks: it plans the steps, calls tools such as your CRM, email or database, checks the results and keeps going until the job is done or it needs a human. That makes agents far more useful, and it is why guardrails, approvals and logging matter so much.

How much does it cost to build a custom AI agent?

Venzpire’s agent builds start at $15,000 for a single workflow with a few tool integrations and run $30,000–$60,000 for customer-facing agents with knowledge bases and approval flows. Market rates for production agents with tool use typically range from $30,000 to $200,000 depending on integrations and risk.

How do you stop an agent from making costly mistakes?

Four layers: the agent only gets the permissions it needs, irreversible actions require human approval, business rules and limits are enforced in plain code rather than prompts, and every release must pass an evaluation suite of real scenarios. Every run is logged so you can see exactly what it did and why.

Which agent frameworks and models do you use?

We choose per project between LangGraph, CrewAI, the OpenAI Agents SDK or a lightweight custom orchestrator, on top of GPT, Claude, Gemini or open-weight models. We keep the design provider-agnostic so you can switch models as prices and capabilities change.

Guides on AI agent development

Have an AI product worth building properly?

Tell us what you are building. Venktesh reads every application himself and replies within one business day.

Apply for a strategy call