By Sahil Kataria, Chief Executive Officer, QServices
Updated June 12, 2026
Sahil Kataria is the CEO of QServices, a Microsoft Solutions Partner delivering AI agents and custom software for regulated industries. He leads enterprise AI strategy and FinTech delivery. LinkedIn ↗
Written from QServices' hands-on delivery work and reviewed by Rohit Dabra, Chief Technology Officer, QServices, before publishing.
QServices is a remote-first software consultancy serving Austin businesses in tech, healthcare, and real estate. We are not based in Austin, but we run Azure AI Foundry engagements with Central Time hours overlap and full compliance support for the Texas Data Privacy Act and Texas Department of Insurance (TDI) regulations.
What Austin buyers typically need from Azure AI Foundry
Austin's tech companies, healthcare providers, and real estate firms each bring distinct requirements to an Azure AI Foundry project. Here is what we see most often across these three industries:
- Tech companies and SaaS platforms: Building internal knowledge bots, automating DevOps workflows, or adding AI features to existing Azure-hosted products. Getting the evaluation pipeline right matters here. Production apps need to measure accuracy over time, not just ship a demo.
- Healthcare providers and health-tech startups: AI-assisted clinical documentation, patient triage support, or internal knowledge retrieval. Federal HIPAA applies to patient data. For insurance-adjacent products, TDI adds its own oversight layer on top. We scope compliance overhead into every healthcare engagement from the start, not as a post-launch addition.
- Real estate platforms and PropTech: Lease abstraction, contract review, and property data extraction using Azure AI Search backed by Foundry. The Texas Data Privacy and Security Act, effective July 2024, requires data minimization and consumer rights workflows for any app processing personal data of Texas residents.
A pattern common across all three: teams that have already used Azure OpenAI directly but hit evaluation and observability gaps when moving to production. Azure AI Foundry addresses that gap, but only if the evaluation pipeline is configured from day one, not retrofitted after launch. This is one of the most consistent mistakes we see in Foundry projects.
How we work with Austin clients
Our team maintains Central Time hours overlap. During CDT (March through November), India Standard Time is 10.5 hours ahead of Austin. Our engineers are online in the evening IST, which aligns with Austin morning business hours from roughly 8 AM to 11 AM CT, giving you 2 to 3 hours of synchronous overlap daily. During CST (November through March), IST is 11.5 hours ahead, shifting that window by one hour. Most Austin clients schedule a 9 AM CT standup and use Microsoft Teams or Slack for async updates throughout the day.
Typical engagement cadence for an Azure AI Foundry project:
- Week 1 to 2: Discovery and architecture review, shared Azure subscription setup, access provisioning, compliance scoping for any HIPAA or TDI-regulated workloads.
- Weekly: 30-minute standup at agreed CT time, async PR reviews, Loom walkthroughs for complex changes.
- Bi-weekly: Demo of working increment, backlog grooming, sprint planning.
- Milestone reviews: We can join on-site in Austin for major deliverables on longer engagements if scheduled in advance.
Pull requests are reviewed within 24 hours, not batched. For code paths handling personal data under the Texas Data Privacy and Security Act, we flag changes for your internal security team's review before merge.
Relevant work in similar markets
We do not currently have a client in Austin or Texas. Our closest work is in SaaS and IT services, which overlaps with Austin's tech sector. For Austin teams building AI agents on Azure, our AI agent development service page covers related project patterns in detail.
Case Study
AI Project Management Bot for Azure DevOps and MS Teams (Smart PM)
IT services company
Automated meeting transcript capture and backlog creation in Azure DevOps with Fibonacci story point assignment and sprint capacity tracking
Real-time Power BI sprint velocity dashboards replacing manual meeting note capture and task allocation
For an IT services company, we built a Smart PM Assistant on Azure AI Foundry, Azure AI Search, Power Automate, and Azure DevOps APIs. The system automated meeting transcript capture via the Fireflies.ai API, created backlog items with Fibonacci story point assignments, and fed real-time sprint velocity data into Power BI dashboards. The client's engineering team stopped manually allocating tasks from meeting notes within the first sprint.
Case Study
Enterprise Knowledge Management Bot (Copilot Studio + Azure AI Foundry)
Enterprise software company
Accurate, prompt responses for both document-specific queries and broader general knowledge questions from a unified AI assistant
Microsoft Copilot StudioAzure AI FoundryAzure AI SearchGPT-4o
For an enterprise software company, we delivered a knowledge management bot using Microsoft Copilot Studio and Azure AI Foundry with GPT-4o. The bot answered both document-specific and general knowledge queries from a single interface, replacing a fragmented internal wiki search that had been returning irrelevant results.
Neither engagement was in Austin, and we will not suggest otherwise. If you want to speak with a reference client before committing, we can arrange that through the discovery call.
What Azure AI Foundry costs for a typical Austin project
Azure AI Foundry engagements for Austin clients typically fall in the $25,000 to $120,000 range, paid in USD. Scope determines where your project lands:
- Focused build ($25,000 to $40,000): Single use case, existing Azure subscription, one or two integrations. Typically 8 to 10 weeks.
- Standard engagement ($40,000 to $80,000): Two to three integrated systems, evaluation pipeline setup, observability configuration. 10 to 14 weeks.
- Full production deployment ($80,000 to $120,000): Multi-agent build, compliance review, full evaluation pipeline, post-launch monitoring. 14 to 16 weeks.
For healthcare and insurance projects in Texas, budget an additional 15 to 25 percent for HIPAA scoping and TDI compliance review. Each non-trivial system integration (EHR, CRM, Azure DevOps) adds $3,000 to $12,000. A production-grade evaluation pipeline setup adds $5,000 to $15,000 on top of base scope. For Texas Data Privacy and Security Act compliance review, add $5,000 to $20,000 depending on data volume and processing scope.
See our full Azure AI Foundry cost breakdown for a detailed estimate guide. Post-launch maintenance retainers run $2,000 to $4,000 per month.
How to start working with us
Three steps to get started:
- Discovery call (30 minutes): You describe the use case and current Azure setup. We ask about compliance requirements, existing integrations, and internal team capacity.
- Scoping document: Within five business days, we send a written scope covering architecture, timeline, cost range, and key assumptions. No obligation on your side.
- Project start: Once the statement of work is signed, we provision the shared Azure environment and begin sprint 1 within one week.
Can Austin companies work with a remote Azure AI Foundry team?
Yes. We maintain Central Time hours overlap, run standups and demos over video at agreed CT times, and use Microsoft Teams or Slack for async communication. For Texas clients handling personal data, we sign data processing agreements that address Texas Data Privacy and Security Act obligations. For TDI-regulated insurance projects, compliance review is built into the statement of work from the start, not added as a line item later.
We do not have a physical office in Austin. On-site visits for milestone reviews or stakeholder presentations can be arranged with advance notice, billed at travel cost. For most Austin clients, the remote model covers everything without any on-site component. The 9 AM CT daily overlap window handles what needs to be live.
Ready to discuss your project?
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Frequently Asked Questions
Do you have an office in Austin? +
No. QServices is a remote-first consultancy based in India. We work with Austin clients on fully remote engagements with Central Time hours overlap. On-site visits for milestone reviews can be arranged with advance notice, billed at travel cost. Most Austin clients run the full engagement without any on-site component.
What is the time difference between Austin and your team? +
During CDT (March through November), India Standard Time is 10.5 hours ahead of Austin. During CST (November through March), IST is 11.5 hours ahead. We schedule morning standups IST that land in Austin's early business hours, giving you 2 to 3 hours of live overlap daily, typically around 8 to 11 AM CT.
Have you worked with companies in Austin or Texas before? +
We do not have a current Austin or Texas client to reference. Our closest work is with SaaS and IT services companies: a Smart PM Assistant on Azure AI Foundry for an IT services firm, and an enterprise knowledge bot for an enterprise software company. Both involved Azure AI Foundry in production with evaluation pipelines. We can arrange reference calls through the discovery process.
How do you handle Texas Data Privacy Act compliance for Austin clients? +
The Texas Data Privacy and Security Act, effective July 2024, requires data minimization, consumer rights workflows, and clear processing agreements. We document our data handling practices and sign data processing agreements. For insurance-adjacent projects under TDI oversight, compliance review is scoped into the statement of work before development starts, with an additional 15 to 25 percent budget allocation.
What industries do you serve in the Austin market? +
In Austin, we focus on three industries that match our Azure AI Foundry work: tech and SaaS companies building AI-powered products on Azure, healthcare providers and health-tech startups requiring HIPAA-compliant AI applications, and real estate platforms using Foundry for lease abstraction, contract review, and property data extraction.