Focused LLM applications first release
A scoped engagement that ships the core outcome first — then iterates with stakeholder feedback and written next steps.
Service
Generative AI & LLM Apps
Custom LLM apps and copilots grounded in your data — delivered with safety and cost discipline.
What this means in plain terms
Mak IT Solutions delivers LLM applications as a structured studio engagement — discovery, design, implementation, QA, and handover — not a loose collection of freelance tasks.
Custom LLM apps and copilots grounded in your data — delivered with safety and cost discipline.
Stakeholders receive a written plan, demoable milestones, and documentation so internal teams can operate the result confidently after go-live. When adjacent technologies are a better fit, we say so; when this capability is the right path, we staff and deliver it with clear ownership.
Who this is for
If any of these sound like your organization, this engagement is a fit.
- Product teams embedding copilots
- Internal tools for knowledge work
- Support and sales assist use cases
- Companies moving from chatbot demos to product features
Problems we solve
Common blockers we address up front in structured delivery.
Unclear starting point
We define the first release and success criteria before build begins.
Delivery risk
Milestone demos and quality gates keep progress visible to stakeholders.
Handover gaps
Documentation and training so your team is not dependent on a single contact.
Tooling confusion
We recommend (or fit) technologies your organization can own long term.
What you get
Concrete delivery areas typically included when organizations engage Mak IT Solutions for Generative AI & LLM Apps.
- Scoped LLM applications roadmap and success criteria
- Solution design and implementation
- Integrations and data wiring as needed
- QA, launch readiness, and stakeholder demos
- Documentation and team handover
- Optional post-launch iteration support
How we work
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1
Discover goals, constraints, and success metrics for LLM applications
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2
Design the approach, UX (where relevant), and delivery plan
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3
Build in iterative releases with quality gates and demos
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4
Launch, measure outcomes, and hand over with clear ownership
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Samples
How engagements usually look
Representative engagement patterns for Generative AI & LLM Apps — scope and timeline vary by goals and constraints.
LLM applications modernization
Upgrades to performance, UX, and integrations that make an existing capability easier to operate and grow.
LLM applications for scale
Architecture and delivery work to support higher usage, clearer admin operations, and safer iteration.
FAQ
Questions about Generative AI & LLM Apps
Clear answers before you kick off.
Discovery, solution design, implementation, QA, and launch support tailored to LLM applications. Decisions are documented and handed over so your team can operate the result confidently.
Packages
Add AI to your business
Give your team (or customers) a smart assistant that knows your company — without replacing the people who still need to make the final call.
AI Trial
Try AI on one real business problem before you invest more.
From $2,500 · 2–4 weeks
See what’s different →
Company Knowledge Assistant
Ask questions in plain language — get answers from your own files, policies, and FAQs.
From $5,000 · 4–8 weeks
See what’s different →
AI Helper for Your Team or Customers
A helpful AI inside your website or tools — drafts, answers, and guides people step by step.
From $6,500 · 6–10 weeks
See what’s different →
Customer Chatbot
A chatbot that answers from your knowledge base — and connects customers to a real person when needed.
From $4,500 · 4–8 weeks
See what’s different →
Ready to discuss Generative AI & LLM Apps?
Share your goals and timeline — our team will propose a clear delivery path with milestones.