AI-first · Enterprise · Global

An AI engineering company built for enterprises.

T7 Solution designs, ships and runs production AI systems — LLM apps, RAG pipelines, voice agents, computer vision and forecasting — for enterprise teams that need outcomes, not demos.

What is an AI engineering company?

An AI engineering company is a product-shop hybrid: part machine-learning team, part full-stack engineering team. Its job is to take a business outcome — deflection rate, cycle time, defect leak, forecast MAPE — and ship a production system that moves the metric.

That means retrieval, evals, guardrails and observability are foundational, not afterthoughts. It means the same team that trains and integrates models also owns the UI, auth, integrations and rollback paths. And it means every deployment ships with a measurement plan tied to P&L.

T7 Solution is that team. We ship LLM, voice, vision and forecasting systems for healthcare, retail, manufacturing, logistics and financial services — and we run our own products (Healthtech, ERP, POS, Studio) on the same stack.

How we're different

AI-first stack

LLMs, RAG, vector search, agents, evals and voice are our default toolkit — not a bolt-on to a generic dev shop.

Production-grade delivery

Type-safe code, CI/CD, observability, evals and rollback plans on day one. We don't hand off prototypes.

Governance & evals

Hallucination SLAs, PII handling, DPA-ready deployments and eval harnesses tied to business KPIs.

We ship our own products

T7 Healthtech, ERP, POS and Studio run in production — the same engineering team ships client systems.

Industries we serve

All industries

Healthcare

EHR, clinic management, OCR, and predictive care built by the team behind T7 Healthtech.

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Retail & E-commerce

Hybrid POS, ERP, demand forecasting, and virtual product photography.

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Manufacturing

Production ERP, computer-vision QC, predictive maintenance, and supply-chain AI.

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Logistics

Route optimisation, fleet intelligence, document AI, and shipment forecasting.

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Startups

AI MVPs, LLM-native SaaS, and rapid product engineering for founders.

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Education

LMS, AI tutors, adaptive learning, and student-management systems.

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Legal & LawTech

Contract review, e-discovery, matter management and legal-research copilots.

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Insurance & InsurTech

Claims automation, underwriting copilots, fraud detection and policyholder self-service.

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Real Estate & PropTech

Lead qualification, virtual tours, document automation and predictive pricing for real estate.

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Hospitality & F&B

AI concierge, dynamic pricing, kitchen automation and review-response copilots.

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Media & Entertainment

Content generation, moderation, metadata enrichment and recommendation systems.

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Energy & Utilities

Predictive maintenance, load forecasting, asset inspection and safety analytics.

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Agritech

Yield prediction, pest detection, satellite analytics and farmer voice agents.

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GovTech & Public Sector

Citizen chatbots, grievance triage, document digitisation and predictive public-service delivery.

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Telecom

Network anomaly detection, customer self-service, churn prediction and fraud analytics.

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Professional Services & Consulting

Proposal copilots, knowledge management, research automation and utilisation forecasting.

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How we engage

Three shapes of engagement, mapped to where you are in the AI journey — from first audit to embedded delivery.

Discovery Sprint

2 weeks

AI readiness audit, opportunity mapping, ROI model and a scoped pilot plan.

  • Data & integration audit
  • Use-case prioritisation
  • Scoped pilot proposal
  • Executive readout
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Build & Ship

6–12 weeks

We design, build and deploy a production AI system to a defined KPI, with evals and observability.

  • End-to-end delivery
  • Eval harness + KPIs
  • CI/CD + observability
  • 60-day hypercare
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Embedded AI Team

Quarterly

A pod of AI engineers embedded with your team — retained capacity for building, iterating and running AI systems.

  • Dedicated pod (2–5)
  • Weekly velocity reviews
  • Roadmap co-ownership
  • SLA on incidents
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Frequently asked questions

What is an AI engineering company?

An AI engineering company designs, builds, deploys and runs production AI systems — LLM apps, RAG pipelines, voice agents, computer vision, forecasting — with the software engineering rigor of a modern product team. Unlike a research lab or a staff-aug shop, we own outcomes end-to-end.

How is T7 different from a generic software agency?

Generic agencies treat AI as a checkbox. Every T7 engagement starts from an AI-first architecture: retrieval, evals, guardrails and observability are foundational, not added later. Our team ships LLM, voice and CV systems every week.

How is T7 different from a pure MLOps or data-science consultancy?

Data-science consultancies deliver notebooks and models; MLOps shops deliver pipelines. T7 delivers full products — UI, integrations, auth, observability and iteration — with AI models as one component of a shipped system.

What does an AI project typically cost?

Every AI project is custom scoped during a free discovery call based on data readiness, integration surface, and technical complexity. We align our services to your specific business outcomes.

How long does a pilot take?

Most pilots go from kickoff to a measurable result in production within 4–8 weeks. Discovery is 2 weeks; build is 4–6.

Do you sign DPAs, BAAs and NDAs?

Yes. We sign DPAs, NDAs and HIPAA BAAs, deploy in the client's cloud region when required, and support on-prem and air-gapped setups for regulated workloads.

Do you work with our existing data / platform team?

Yes — most engagements are collaborative. We plug into existing data warehouses, CI/CD, IAM and observability stacks, and hand off runbooks + evals at every milestone.

Where is the team based?

Engineering is based in Ahmedabad, India with delivery leads across India, the UAE and remote. We serve enterprise clients in North America, EMEA and APAC in overlapping timezones.

Ready to Build Your AI Product?

Talk to a senior AI consultant from T7 about your industry, workflow, or product idea. Free, no commitment — reply within one business day.

  • · AI feasibility & architecture review
  • · Product / MVP roadmap
  • · Integration & automation strategy