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espialtech

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Start a Project
AI systems,
running in production

Twenty-plus engagements across manufacturing, energy, retail, logistics and the public sector. A selection is below; the rest are under NDA.

Why Delay Hurts
The longer you wait, the harder
it is to catch up.
Manual Operations Slow Progress
/ 01

80%

/Workload
Competitors Outpace Innovation
/ 02

65%

/Growth
Automation Potential Remains Untapped
/ 03

70%

/Opportunities
Repetition Replaces Creativity
/ 04

49%

/Draining Time
Engagement Models
From pilot to enterprise.
clear scope,
 transparent cost.
Pilot Sprint
Teams validating a first AI use case
from $X,XXX · 4-6 weeks
Start a Pilot
What’s included
Prove the value before you commit the budget. You end with a working prototype, an evaluation rubric, and a clear go/no- roadmap.
  • Discovery workshop
  • Opportunity brief and KPI model
  • Working prototype
  • Eval rubric and baseline
  • 1 data source, 1 integration
  • Go/no-go roadmap
Production Engagement
Organisations putting AI into the business
Custom
Talk to Us
What’s included
Full delivery - build, deploy, calibrate and operate. Multi-environment releases, on-site deployment and one accountable support loop.
  • Everything in Pilot
  • Production build and integration
  • On-site deployment and hardware calibration
  • CI/CD, tracing, alerts, guardrails
  • Full eval dashboard
  • Multiple data sources and integration
  • Ongoing monitoring and tuning
FAQs
Frequently
asked questions
A focused pilot reaches a working, testable v1 in four to six weeks. A production system - with on-site deployment and integration-typically runs eight to twelve weeks depending on hardware, data access and how many systems it has to talk to. We tell you which one you are in during discovery, not after.
A clear problem statement, a definition of success, access to sample data, and one stakeholder who can make decisions. That is genuinely it. We run a kickoff workshop to pin down scope and the KPI model before anyone writes code.
Whichever ones wins on accuracy, latency and cost for your problem. In practice: Claude and GPT for reasoning and generation; Llama and Mistral when it has to be self-hosted; YOLO, OpenCV and InsightFace for vision; PyTorch, ONNX and TensorRT for anything on the edge. We are not loyal to a vendor. We are loyal to the benchmark
Yes, and several of our systems do. We have shipped fully on-premise vision analytics that runs a single executable with no internet connection, and self-hosted voice assistants where every inference endpoint stays inside the customer VM. If compliance rules out third-party APIs, we design for that from the start.
Development is included in the project price. Model and API usage is billed at cost, based on your actual volume. We estimate it up front and then work to bring it down - compression, caching and smaller models where a smaller model is enough.
Monitoring, tuning and one support loop that runs from the engineers who built it. AI system drift-data changes, storefronts change, We watch for it and we fix it.
E-mail address
hello@espialinfotech.com
Phone number
+91 XX XXXX XXXX
Our Location

New Delhi, India

Contact
Let's build
something that ships

Tell us the problem. If AI is the wrong tool for it, we will say so.

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