Our Intent

BE in AI. DO in AI. DELIVER in AI.

Three words define every Daiva engagement — strategy that's honest, engineering that's senior, and outcomes that run in production.

BE

Strategy & Intent

  • AI readiness assessment of your operations
  • Use-case mapping ranked by ROI & difficulty
  • An honest go / no-go — including "not yet"

DO

Engineering & Build

  • Agentic systems on the open stack (MCP · A2A)
  • Evaluation suites & guardrails from day one
  • Weekly demos — working software, not decks

DELIVER

Production & Outcomes

  • Deployment, monitoring & audit trails
  • Your team trained to own & extend it
  • Measured outcomes — cost, accuracy, hours saved

The Problem We Solve

Enterprise AI is stuck in pilot purgatory.

Companies don't fail at AI because the models are weak. They fail because the last mile — integration, evaluation, guardrails, governance — is engineering work most teams haven't done before. That last mile is all we do.

⚠

Pilots that never ship

The demo impressed leadership six months ago. It still isn't touching real workflows. We harden prototypes into systems that survive production traffic, edge cases, and audits.

⛓

AI that can't reach your data

A model that can't read your CRM or write to your ERP is a toy. We build secure MCP integration layers so agents act on your actual systems — with scoped, logged access.

◎

No governance, no trust

4 out of 5 companies deploying agents have no governance model. We ship audit trails, human-in-the-loop approvals, and evaluation suites from day one — because your compliance team will ask.

What We Do

Four ways we engage.

Focused offerings, not a menu of everything. Each one ends with working software in production — not a slide deck.

🤖

Agentic AI Development

Multi-agent systems that plan, execute, and validate real workflows — support automation, document processing, operations copilots — with human oversight built in.

How we build agents →
🔌

Agent Infrastructure — MCP · A2A

The open-standard integration layer for enterprise AI: MCP servers connecting agents to your ERPs, CRMs, and databases, A2A for multi-agent coordination — least-privilege access, full audit logging.

Agent infrastructure →
🚀

Pilot-to-Production Engineering

Already have a stalled AI prototype? We add evaluation frameworks, guardrails, monitoring, and CI/CD to take it live — fixed scope, fixed timeline.

Production engineering →
⚡

AI-Native Product Engineering

Add copilots, RAG-powered search, and intelligent automation to your existing product — no rewrite required. Or build a new AI product with us end to end.

Product engineering →

Why Daiva

Honest answers to "why should we trust a startup?"

We're early-stage, and we won't pretend otherwise. Here's what that buys you.

  • You get the senior team, always. The engineers who scope your project build your project. No bait-and-switch to a junior bench.
  • We're specialists, not generalists. Agentic systems and MCP integration are our entire practice — not one service line of forty.
  • You own everything. Code, models, infrastructure, IP. No lock-in, no licensing traps, full documentation and handover.
  • Fixed-scope discovery first. A 2-week paid discovery sprint produces an architecture, a roadmap, and an honest go/no-go — including "AI isn't the right tool here" when it's true.
  • India build economics, global standards. Senior AI engineering from Bengaluru at a structural cost advantage — without the communication overhead.

Our delivery promise

01

Discovery Sprint — 2 weeks

Use-case mapping, data audit, architecture, ROI model. Fixed price.

02

Build — 4–6 weeks

Agile sprints, weekly demos, working software every Friday.

03

Harden — 2–4 weeks

Evaluation suites, security review, guardrails, monitoring.

04

Production + Handover

Deployment, documentation, training. Optional managed support.

Technology

Model-agnostic. Production-obsessed.

We pick the right model and stack for your constraints — cost, latency, privacy, compliance — not whatever's trending.

ClaudeOpenAI GPTGeminiLlama (self-hosted)MCP (Linux Foundation)A2A ProtocolAP2 PaymentsLangGraphCrewAIPythonTypeScriptPinecone / pgvectorAWS · GCP · AzureDocker · KubernetesMLflowHuggingFace

FAQ

Questions buyers actually ask.

What does an agentic AI development company do?
We build AI systems that plan, reason, and execute multi-step work autonomously — connecting to your CRM, ERP, databases, and APIs to complete real business workflows with human oversight, rather than just answering questions in a chat window.
How long until we're in production?
A typical engagement: 2-week discovery sprint, 4–6 week build, 2–4 weeks of hardening. Production in roughly 8–12 weeks, depending on integration complexity and compliance requirements.
We already have a pilot that stalled. Can you fix it?
That's our most common engagement. Most pilots stall on missing evaluation, guardrails, and integrations — not model quality. We audit what exists, keep what works, and engineer the path to production.
What does it cost?
Discovery sprints are fixed-price. Builds are scoped after discovery so you're never paying for open-ended exploration. We'll give you a straight number after the first call — and we'll tell you if AI isn't the right investment for your problem.
How do you handle data security and compliance?
Least-privilege access for every agent action, full audit trails, human-in-the-loop approval on critical paths, and deployment inside your cloud (VPC) or on-premise when required. We design for your compliance regime — not around it.

Get a free AI Readiness Assessment

A 30-minute call + a short written assessment: where AI will (and won't) pay off in your operations, and what production actually takes. No pitch deck, no obligation.

Request Your Assessment