New OMANGOM is now an OpenAI Select Partner: helping teams build, deploy and scale AI. Read more

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OMANGOM Named an OpenAI Select Partner: What It Means for Our Customers

OMANGOM has been named an OpenAI Select Partner within the OpenAI Partner Network. Here's what that means for our customers, how we deliver AI projects, and a look at a recent engagement where we took an AI assistant from idea to production.

OMANGOM Insights
7 min read

⚡ At a glance

  • OMANGOM has been named an OpenAI Select Partner in the OpenAI Partner Network.
  • Our focus stays the same: AI that works in production and removes real friction for your team.
  • Read how we built a customer support assistant for a growing eCommerce retailer, from discovery to rollout.

The announcement

We’re excited to share that OMANGOM, a software engineering company that designs, builds and scales custom software, SaaS platforms and AI systems, has been named an OpenAI Select Partner within the OpenAI Partner Network.

The OpenAI Partner Network is a global program for partners to build, sell, and deliver AI solutions with OpenAI. It brings together partners with deep industry expertise, delivery capabilities, and customer relationships while equipping them with resources, enablement, and support to help enterprises adopt OpenAI frontier models and products and turn them into measurable impact.

As an OpenAI Select Partner, OMANGOM will continue working with OpenAI to help organizations build, deploy, and scale AI solutions responsibly and effectively. This work will help organizations get more useful work from every token and stronger performance per dollar with GPT‑5.6, while using ChatGPT Work to turn ambitious goals into finished work. For OMANGOM, that means helping startups and mid-sized businesses in healthcare, fintech, retail and eCommerce, education, and logistics and travel put AI agents, LLM integrations, retrieval systems and workflow automation into production.

OpenAI Select Partner

OMANGOM is an OpenAI Select Partner. As part of the OpenAI Partner Network, we look forward to continuing our work with OpenAI to help organizations build, deploy, and scale AI solutions responsibly and effectively.

Learn more about the OpenAI Partner Network →

Being named an OpenAI Select Partner reflects the work our team does every day: helping businesses move from AI experiments to AI that fits into how their teams already work, is safe to put in front of customers, and keeps improving after launch. We look forward to continuing our work with OpenAI to help our customers get there faster. — Sam Aggarwal, CEO, OMANGOM

What it means for our customers

For the companies we work with, this milestone means working with a team that has built with OpenAI’s platform, and that is part of the network OpenAI is building to help businesses adopt AI well. In practice, you can expect:

  • Production-first delivery. We design for reliability, security, cost and measurable outcomes from day one, not just a compelling demo.
  • End-to-end capability. One team for strategy, product engineering, integration with your existing systems, cloud infrastructure and ongoing optimisation.
  • Practical guidance. Honest advice on where AI will make a real difference in your business, and where a simpler solution is the better call.
  • Continuity. We stay with you after launch, monitoring quality and improving the system as your needs and the technology change.

What this partnership is, and isn’t

We believe in being clear about credentials, so here is how we think about this one:

✓ What it is

  • Membership of the OpenAI Partner Network at the Select tier
  • Recognition of our work building AI solutions with OpenAI
  • Access to resources, enablement and support from OpenAI through the network

✕ What it isn’t

  • An endorsement by OpenAI of any specific project
  • A guarantee of results; those come from how the work is done
  • A listing in OpenAI’s Partner Locator, which is reserved for higher partner tiers
  • A reason to use AI where it doesn’t belong

Case study: an AI support assistant for a growing eCommerce retailer

To show what this looks like in practice, here’s a recent engagement. The client name is withheld at their request.

Client snapshot

A multi-brand online retailer in the United States

Industry
Retail & eCommerce
Challenge
Support volume growing faster than the team
Solution
AI support assistant with human handoff
Built with
OpenAI models, order & CRM integrations

The challenge

The retailer was growing quickly, and customer support was struggling to keep up. Most tickets were repetitive: where’s my order, how do I return this, does this size run small. But each one still needed an agent to open three different systems to answer it. Response times went up during sales and holidays, and experienced agents spent most of their day on routine questions instead of the complex cases where they add the most value.

The team had tried an off-the-shelf chatbot before. It followed rigid scripts, couldn’t see real order data, and frustrated customers enough that it was switched off within weeks. They wanted an assistant that could actually help, and that knew when to hand over to a person.

What we built

We designed and built an AI support assistant on OpenAI models, embedded in the retailer’s website chat and their helpdesk. The key design decisions:

  • Grounded in real data. The assistant uses tool calling to look up live order status, shipping and return eligibility from the retailer’s own systems, so answers reflect the customer’s actual order rather than generic policy text.
  • Answers from approved knowledge. Policies, product care guides and FAQs are retrieved from a curated knowledge base, so the assistant stays accurate and on-brand.
  • Clear guardrails. Refunds above a set limit, complaints and anything sensitive go straight to a human agent, along with a summary of the conversation so the customer never has to repeat themselves.
  • Built to be measured. An evaluation set of real (anonymised) customer questions runs on every change, and a dashboard tracks resolution, handoffs and customer feedback.

How we delivered it

  1. Discovery and ticket analysis

    We reviewed historical tickets with the support team to find the questions that were high-volume, low-risk and well suited to automation, and agreed which cases must always go to a person.

  2. Prototype with real data

    A working prototype connected to a copy of order data let the support team try it on real questions within the first few weeks, and shape its tone and behaviour directly.

  3. Hardening and integration

    We added the helpdesk integration, human handoff, access controls, logging and the evaluation suite, and load-tested for peak sales traffic.

  4. Phased rollout

    The assistant launched first for order-status questions, then expanded to returns and product questions as quality was confirmed at each step.

The outcome

⚡

Faster answers for customers

Routine questions like order status and returns are now answered instantly, day or night, including during peak sales.

🤝

Agents focused on what matters

The support team spends far less time on repetitive lookups and more on complex cases and at-risk customers.

🔁

Seamless human handoff

When a person is needed, agents receive the full context and a summary, so conversations pick up where they left off.

📈

Room to scale

Support capacity now grows with the business without hiring at the same pace, and every new question type goes through the same evaluation process.

What stood out was that they started with our support team, not the technology. The assistant sounds like us, knows our policies, and knows when to step aside. — Head of Customer Experience, DJI Mexico

How we deliver AI projects

The case study above follows the same approach we use on every AI engagement, whether it’s an assistant, an agent, a retrieval system or workflow automation:

StageWhat happensWhat you get
DiscoverIdentify the workflows where AI removes real friction, and the risks to manageA prioritised use-case shortlist and success metrics
PrototypeBuild quickly against real data with the people who’ll use itA working prototype and early quality benchmarks
ProductioniseIntegrations, guardrails, security, evaluation and monitoringA reliable system ready for real users
ScalePhased rollout, cost tuning and continuous improvementGrowing impact, with quality you can measure

Have an AI use case in mind?

Talk to our team about taking it from idea to production.

Book a consultation

Looking ahead

Becoming an OpenAI Select Partner is a milestone, not a finish line. Looking ahead, OMANGOM plans to expand its OpenAI-based offerings, invest in our team’s skills and enablement, and scale customer deployments, helping customers translate AI ambition into business outcomes. We’ll keep sharing what we learn here on the blog, including architecture guides like our practical guide to production-ready RAG systems.

Thank you to our clients, who trust us with their most important problems, and to our engineers, whose work made this possible. If you’re exploring what AI could do for your business, we’d love to talk.

Learn more about the OpenAI Partner Network: openai.com/business/partners


OpenAI, ChatGPT, GPT and the OpenAI logo are trademarks of OpenAI.

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