Applied AI for ops, support, and product teams

Production AI that cuts manual work — shipped in weeks, not quarters.

We build retrieval, automation, and agent systems inside your repo. First useful automation lands in 2–3 weeks, full rollout in 8–12. Senior pod, no hand-offs.

See what we ship

What teams get

First useful automation

2-3 weeks

Typical production rollout

8-12 weeks

Delivery model

Senior pod in your repo

What we ship star

Five problem shapes we solve well

Workflow automation

Replace repetitive ops work with measured automations. We track hours saved, not tickets closed.

LLMs and custom models

Custom models and retrieval pipelines tuned to your data, with evaluations you can defend.

Internal copilots and assistants

Domain-aware assistants for your team, scoped to one job they can do reliably.

Content systems and personalization

Production content pipelines with quality gates — tone, accuracy, and brand checks built in.

AI strategy and architecture

A two-week diagnostic that ends in a one-page plan: where AI pays back, where it doesn't, and what to build first.

Work shipped star

What we've actually shipped

AI Assessment Engine

Autonomous scoring engine for descriptive and essay responses with personalized feedback loops to improve learner outcomes.

Review Response Assistant

AI assistant that monitors and responds to public reviews across listing platforms to improve response speed and brand consistency.

Seizure Detection Pipeline

Medical-grade machine learning pipeline combining CNN and K-Means models, delivered with production handoff for a pharma stakeholder.

Testimonials star

What people say about us

Aayush's work has been indispensable to the progress of our project. He expertly set up and maintained organizational tools while providing sophisticated coding solutions throughout our machine learning pipeline. His technical expertise combined with his collaborative approach made him an invaluable asset to our research team.

Dr. Rasmus Herlo

Post-Doc at University of Copenhagen

Aayush demonstrated exceptional analytical abilities in his research on AI tutoring systems. His systematic comparison of human and AI teaching patterns revealed critical insights that advance our understanding of educational technology. His work shows a rare combination of technical mastery and thoughtful consideration of human-AI interaction—precisely the skillset needed to build AI systems that truly serve human needs.

Dr. Nitin Sawhney

Professor at Aalto University

Working with a technology partner is often a headache—requirements keep changing, and communication gaps are common.Futurebits is the only vendor I've worked with where documentation is so strong that nothing gets lost in translation. Their first-principles thinking and deep discussions help clarify evolving needs.They tick all the right boxes: extremely talented (Decoding Me's website and dashboard are loved by all), prompt, dependable, and truly trustworthy with time and money.

Khushbu Chopda

Founder, Decoding Me

Futurebits delivered exceptional work ahead of schedule, making the entire experience truly seamless. Their adaptability to evolving requirements and collaborative approach greatly contributed to the project's success. A dependable and efficient partner—we sincerely value their contribution.

Vinod Bombale

Portfolio Manager - Global Pricing Innovation

Ways to work with us

Three ways in. All senior, all scoped.

Pick the smallest one that proves the bet. We'll tell you on the first call which model actually fits.

Sprint

2 – 4 weeks

A clear, scoped problem. Land one shipped artefact fast.

One shipped surface — a flow, a prototype, an automation
A short post-mortem with what we'd do next and why
Daily async updates, one weekly working session

Pod

8 – 12 weeks

A 0-to-1 launch or a meaningful 1-to-10 jump. We embed alongside your team.

A senior pod (design, engineering, AI) running end-to-end
Weekly demo cycle, fortnightly steering committee
Hand-off docs your team can keep running with

Partner

Ongoing

Long-running product or platform work. Compounding output, not vendor billable hours.

Senior team allocated as a fractional product unit
Quarterly OKRs tied to your business metrics
Right of first refusal on new bets, shared roadmap ownership

Not sure which fits? Most teams start with a Sprint and graduate.

Book a 30-min AI working call

FAQ

The questions everyone asks (and our actual answers).

What kind of AI projects do you ship?

Production AI systems for support, operations, and product workflows — including retrieval pipelines, evaluations, guardrails, and observability. We prioritize measurable business outcomes over demos.

Can you work with our existing engineering team?

Yes — most of our pods do. We pair with your engineers, write code in your repo, and follow your review process. The goal is your team is stronger when we leave.

How quickly can we expect ROI from an AI engagement?

Most teams see first useful automation in 2-3 weeks. Full production rollouts typically land in 8-12 weeks depending on integrations and governance requirements.

What does an AI engagement usually cost?

Sprints typically start in the low five figures USD; pods scale with scope and complexity. We share indicative pricing on the first call and a fixed proposal within a week.

Do you replace our existing engineering team?

No. We pair with your engineers in your repo, follow your review process, and aim to leave your team stronger than we found it.

Still have a question? Ask Futurebits directly.

I lead AI at Futurebits. We build production systems — retrieval, agents, evals — for ops, support, and product teams. The work I'm proudest of: LLM behavior research, AI in healthcare, and applied modelling that actually shipped.

We take engagements where AI clearly pays back. If your problem is better solved another way, we'll tell you on the first call. No theatre.

- Aayush KucheriaAI Lead, Futurebits — production AI, evals, applied research.

Stop running operations on browser tabs.
Run them on systems we build with you.