✦ AI engineering for software teams

Ship your next AI feature.
Without hiring an AI team.

AIVETech helps software teams and SaaS businesses build, integrate, evaluate and deploy AI features into existing products.

Discuss an AI Project → Explore Our Work

One agreed feature. Direct access to founder Kartik Malhotra. Scope, price and acceptance criteria agreed before implementation.

See what an AI Feature Sprint includes →

Built on
PythonFastAPILangChainQdrantSupabaseElevenLabsPostgresDocker
Start with one feature

AI Feature Implementation Sprint.

For founders and engineering teams with a product to improve or a new product to build. Turn one defined problem into an integrated feature, with scope and acceptance criteria agreed first.

Define the feature

Review your workflow, data and systems. Agree architecture, deliverables, exclusions, evaluation cases and price before implementation.

Build and evaluate

Implement the agreed feature and integrations. Review working increments and test supported inputs, failure handling and output quality.

Deploy and hand over

Deploy to the agreed environment with source and operating documentation. Define ownership and any ongoing support in the proposal.

You supply representative data, system access and feedback. Timeline depends on scope and readiness; model and hosting costs are agreed separately.

See deliverables, responsibilities and acceptance criteria →

Our work

Inspect the work.
Understand the limits.

A founder-built product and a small interactive sample show different kinds of evidence. Neither is presented as paid client work.

Founder-built SaaS · public product and fictional demo

Soil: customer commitment tracking

Customer promises can become disconnected from engineering work. Soil tracks the promise, owner, deadline and supporting evidence, with customer delivery confirmed separately.

Built by Kartik Malhotra. The implementation includes workspace accounts, manual commitments, reviewed Slack candidates, linked work, source-access checks and approval steps for external actions.

Explore the engineering →Open Soil’s fictional demo ↗

What this demonstrates

  • Product UI backed by application logic and PostgreSQL storage.
  • Integrations, permission-aware evidence and action review.
  • Tests covering delivery workflows and access boundaries.

Current limits: the public demo uses fictional data. Available evidence depends on connected tools and permissions. Commitment tracking works without an AI model; optional AI features are separate.

Visit meetsoil.com ↗

Try the clinic receptionist sample Scripted browser demonstration

Clinic front-desk workflow

Scripted chat · fictional clinic · no real bookings

Try “hours”, “fees” or “book at 7pm”. Do not enter personal or health information.

What can I try?
Ask about sample hours or fees, or select a fictional appointment time. No appointment will be booked.

The problem and the implementation

A clinic front desk answers repeated questions and collects appointment requests. This sample illustrates that conversation using local JavaScript rules and fixed responses.

What it does

Recognises hours, fees, location and appointment phrases, then displays a fictional response. Text stays in the page and is not stored or sent to a model.

What it does not do

No voice, AI inference, calendar, WhatsApp or staff connection. It cannot make a real booking or provide clinical advice.

Discuss an AI Project →

A connected system would need an agreed booking API, consent and data handling, escalation rules and evaluation before release.

What we build

Choose the problem. We build the AI layer.

These are example feature types within the same scoped engagement. The right approach depends on your product, data and requirements.

Agents that use your tools

Let users complete a defined task across your systems, with approved actions, retries and human review where needed.

Voice intake & routing

Handle routine intake questions and route callers to the right next step. Language, telephony and latency requirements are evaluated for your use case.

Answers from your documents

Help customers or staff find answers in authorised source material, with citations, permission checks and quality evaluation.

Less repetitive operations

Extract information, prepare a follow-up or move a record between tools. Agree the rules, review points and failure handling first.

Useful summaries & dashboards

Bring selected data into a reviewable view, with AI summaries where they help. Define freshness and source requirements with your team.

Integration into your product

Connect the feature to your existing authentication, data and APIs. Agree deployment, monitoring and handover responsibilities.

Who this is for

A defined problem. A product to improve.

A useful starting point is one workflow with a clear owner, usable data and a result you can test.

You have an existing product

Add document search, a task agent or an automation without replacing the systems your team already uses.

You are building a new product

Define the first AI-powered workflow, validate the data and agree what must work before you expand it.

Your prototype needs delivery work

Review flaky outputs, integration gaps or unclear operating costs. Start with a diagnosis and an agreed next step.

You will need a decision maker, access to relevant systems and time for review. If the data, permissions or intended use make AI unsuitable, the scope conversation should surface that first.

How an engagement works

Know what you’re buying.
Review what gets built.

The proposal defines what is included, how progress is reviewed and how the finished work will be accepted.

STEP 01

Understand

Review the product, users, workflow, data and constraints. Identify one outcome worth testing.

STEP 02

Agree

Write down scope, price, milestones, acceptance criteria, dependencies and exclusions.

STEP 03

Implement

Build the agreed functionality in reviewable increments. Record decisions and progress at the agreed cadence.

STEP 04

Verify

Run representative cases, failure paths and integration checks. Review quality and operating requirements against acceptance criteria.

STEP 05

Hand over

Provide agreed source code, configuration guidance, documentation and ownership details.

STEP 06

Deploy with your approval

Review the release and rollback plan with you. Deploy only after approval; define ongoing support separately.

New requirements are recorded as scope changes. Agree the effect on price and milestones before that work begins. Hosting, model-provider costs and support terms belong in the proposal.

Read the full scope and handover details →

Data, access and reliability

Set the boundaries.
Test the failure paths.

Controls are chosen for your deployment and recorded in the scope. No certification or guarantee of model accuracy is implied.

Control data and credentials

Map where data is processed and retained. Use test data where possible, share API credentials through an agreed secure channel, and grant only the access the integration needs.

Review actions and outputs

Define permission checks and human approval points. Test representative questions, unsupported requests, service failures and recovery paths before acceptance.

Know who operates it

Agree provider accounts, monitoring, rollback and support ownership. Handover covers the agreed configuration and operating guidance; ongoing maintenance is explicit.

For technical depth: agent guardrails · retrieval evaluation · voice latency

Kartik Malhotra, Founder & Principal Engineer at Aivetech
Who leads your engagement

Work directly with the engineer responsible for delivery.

I’m Kartik Malhotra, founder of AIVETech and builder of Soil. I lead the scope, architecture and implementation. You discuss trade-offs with the person building the feature, with review points and ownership agreed from the start.

Kartik MalhotraFounder & Principal Engineer · Aivetech
Connect on LinkedIn

See the founder-built product and technical evidence →

Before you enquire

Clear answers to practical questions.

Can you work inside our existing product?

Yes, subject to a technical review of your code, authentication, data and APIs. We can also scope the first workflow for a new product. We agree the integration and deployment environment before implementation.

What do we receive?

The agreed feature and integrations, tests and evaluation results, source code, configuration guidance and handover documentation. The proposal lists the exact deliverables, acceptance criteria and exclusions.

How do pricing and timelines work?

Both depend on feature scope, data readiness and access. We review the requirements, then agree price and milestones before implementation. There is no advertised fixed price or guaranteed delivery window.

What if the scope changes?

We record the new requirement and agree its effect on price, milestones and acceptance criteria before starting the additional work.

How is our data handled?

We review the data flow, access permissions, AI provider policies and retention needs with you. Credentials are shared through an agreed secure channel. Regulatory and security requirements must be scoped for the specific deployment.

What happens after delivery?

We hand over the agreed code and documentation and deploy with your approval. Warranty, monitoring, maintenance and support hours are defined in the proposal. Ongoing support is a separate agreement.

Is the work shown here paid client work?

Soil is a founder-built SaaS product. Its public demo is fictional. The clinic receptionist is a scripted browser sample. Neither is presented as a paid client deployment.

What happens after I enquire?

Kartik reviews your brief and replies by email with questions or a proposed scoping conversation. We agree any paid work separately; submitting the form does not commit you to a project.

Building for clients? Explore the AIVETech Partner Program for agencies and consultancies →

Get in touch

Tell us what you want to build.

Share the problem, your existing systems and what success would look like. Kartik will review your brief and email you with questions or a proposed scoping conversation. Submitting does not commit you to a project.

WhatsApp / Phone
+91 79066 81979
Based in
India · clients worldwide
Response
Kartik reviews the brief and follows up by email

We use these details to assess and respond to your project. Please do not include credentials, confidential documents or patient data. Privacy details.