AI Consulting Services
Find where AI will pay off in your business, prove it on your own data, and leave with a roadmap you can fund in stages.
OZRIT's AI consulting team works with leadership, operations and IT to choose the right use cases, check data readiness and plan delivery. Because the same engineers build what we recommend, the roadmap is one we can actually deliver.
Tell us what you need
A consultant replies within one business day. No sales deck.
- 17+years building softwareFounded in Hyderabad in 2009
- 500+in-house engineersFull-time, not freelancers
- ISO/IEC 27001:2022certifiedFor information security
- 98%client retentionLong-term partnerships
AI consulting and development, in plain terms
Most AI budgets are lost before a model is built, on use cases nobody tested.
AI consulting services help you decide what to do with AI, in what order and with what evidence. That means listing the ideas, scoring each on value and risk, checking whether the data and systems can support them, and choosing one or two to prove first.
The advice only helps if it can be built. OZRIT combines AI consulting and development in one team, so every recommendation comes with a realistic effort, a technical approach and a view on running cost. We will also tell you plainly when AI is not the right answer and a simpler fix will do.
A typical engagement is short and concrete: a discovery workshop, a data and readiness review, a scored shortlist, a small proof of concept on your own data and a phased roadmap. You can stop after any stage, or move straight into building with the same team.
- Use-case workshops
- AI readiness and data assessment
- Value and risk scoring
- Build, buy or integrate
- AI strategy and roadmap
- Proof of concept
What our AI consulting services include
Each piece produces something you can use, whether or not you build with us.
Use-case workshops
Sessions with your teams to list problems and opportunities, then group them into ideas that AI could address.
AI readiness and data assessment
A review of your data quality, access, privacy position, systems and skills, with the gaps spelled out.
Value and risk scoring
Each idea is scored on expected benefit, effort, data fit and risk, so the shortlist is not a guess.
Build, buy or integrate
An honest comparison of custom development, ready-made tools and adding AI to what you already run.
AI strategy and roadmap
A phased plan with sequencing, owners, budget ranges and the evidence that will unlock each next phase.
Proof of concept
A small working build on your own data that shows whether an idea delivers before you scale it.
Governance and responsible AI
Policies for data use, review, bias, safety and vendor choice that your legal and security teams can sign off.
Team enablement and handover
Training and documentation so your people can run, extend or commission the work afterwards.
How an AI consulting engagement runs
Six stages, each with a clear output and a point where you can stop or continue.
Assess and decide
Usually 2 to 6 weeks
- 1
Understand the business
We learn your goals, constraints, teams and existing systems before we suggest anything.
- 2
Workshop and long list
We run workshops to gather problems and ideas from the people who do the work.
- 3
Score and shortlist
We score each idea on value, effort, data fit and risk, and agree a shortlist with you.
- 4
Check data and feasibility
We test whether the data and systems behind each shortlisted idea can support it.
- 5
Prove one use case
We build a small proof of concept on your own data and measure the result.
- 6
Roadmap and handover
You receive a phased roadmap, budget ranges and documentation, ready to fund or to hand to us.
Where AI consulting helps most
Common starting points, by area of the business.
Operations
Find the manual, repetitive steps where automation or prediction would free the most time.
Customer service
Decide which questions an assistant can resolve and which need people, and what that is worth.
Sales and marketing
Judge where lead scoring, personalisation or content drafting would change results.
Finance and risk
Assess fraud signals, forecasting and document processing against your controls.
Product and engineering
Plan which AI features belong in your product and how to build them without overspending.
Leadership and strategy
Build a board-ready view of AI opportunities, risks and investment, with evidence behind it.
AI consulting for your industry
The same build applies across sectors, but the data, rules and risks differ. These are the industries where we are asked for it most.
Fintech app development
Fraud signals, credit scoring, document checks and support assistants for lenders, payments and banks.
Healthcare app development
Record summaries, triage support, scheduling and personalised plans for providers and health-tech teams.
Retail and eCommerce app development
Product search, recommendations, demand forecasting and support assistants for stores and marketplaces.
Logistics app development
Route planning, ETA prediction, proof-of-delivery checks and exception alerts for fleets and supply chains.
Education app development
Tutoring assistants, content generation, assessment help and engagement analytics for learning platforms.
Real estate app development
Lead qualification, property search, valuation support and document handling for developers and brokers.
What decides the cost of AI consulting
Consulting is scoped by how much needs to be assessed and how deep you want to go.
Breadth of the review
One department takes less time than a company-wide opportunity scan.
State of your data
Data spread across many systems takes longer to assess than a single clean source.
Proof of concept depth
A scripted demo costs less than a test on your real data against a baseline.
Stakeholders involved
More teams and sign-offs mean more workshops and alignment time.
Regulatory context
Regulated sectors need extra review of privacy, audit and model-risk questions.
Handover and training
Enablement for your own team adds sessions and documentation.
Security and privacy in AI consulting
A security or compliance team will ask where the data goes, who can see it and how quality is checked. These are the safeguards we build into every project.
Where your data lives
Models can run in your own cloud account or on private endpoints, with provider settings that stop your data being used for training. You choose the region.
Access control
Assistants respect the permissions of the person asking. Someone who cannot open a document cannot get its content through a chat window either.
Testing before launch
We build an evaluation set from your real cases and measure accuracy, safety and cost before and after every change, not just once at launch.
Certification and ownership
OZRIT is ISO/IEC 27001:2022 certified for information security. You own the code, prompts, models you commission and your data.
All eight AI safeguardsCertifications and AI frameworks we work to
AI consulting services: frequently asked questions
Straight answers on cost, timelines, data, security and ownership.
What do AI consulting services include?
They typically include use-case workshops, a data and readiness assessment, value and risk scoring, a build-buy-integrate comparison, a proof of concept and a phased roadmap. The aim is a decision you can defend, with evidence from your own data.
How is AI consulting different from AI development?
Consulting decides what to build and in what order. Development builds it. At OZRIT the same engineers do both, so a roadmap comes with realistic effort and technical detail, and you can move into delivery without re-explaining everything.
How much do AI consulting services cost?
It depends on the breadth of the review and how deep the proof of concept goes. A discovery sprint from $1,000 is the usual entry point, and it ends with a scoped quote for whatever comes next.
How long does an AI consulting engagement take?
A focused engagement usually takes 2 to 6 weeks, from the first workshop to the roadmap. A proof of concept on your own data typically adds 4 to 8 weeks, and we agree the timeline before you start.
Do we need a lot of data before we start?
Not necessarily. Many useful AI features rely on pre-trained models plus your own documents, which needs far less data than training from scratch. The readiness review tells you plainly what is possible with what you have.
Will you recommend AI even when we do not need it?
No. If a rule, a report or a better workflow would solve the problem more cheaply, we say so. Recommending the simplest approach that meets the goal is part of the service.
Can you help us choose between custom AI and ready-made tools?
Yes. We compare custom development, off-the-shelf products and integration into your existing software on cost, fit, risk and long-term ownership, and we show the comparison to you.
Do you cover AI governance and responsible use?
Yes. We help define policies for data use, human review, bias, safety, vendor selection and monitoring, so that security and legal teams can approve what is built.
Do you work with startups as well as enterprises?
Yes. Startups usually need a fast, narrow answer on what to build first. Enterprises need alignment across teams, integration planning and governance. We adjust the depth and the pace.
Can we hire you for delivery after the consulting phase?
Yes, but it is not required. You can take the roadmap to another vendor or your own team. If you continue with OZRIT, the same engineers carry on, and you can add AI engineers to your team in 10 to 15 business days.
Start with a free AI consultation
Tell us about your business and where you suspect AI could help. A consultant will tell you plainly what is worth testing first and what a first step would cost.
What happens next
- 1An AI consultant reads your note and may reply with a few questions.
- 2We hold a call to understand the problem, your data and the systems involved.
- 3If AI fits, we propose a discovery sprint or a scoped pilot with clear success measures.