// AI Engineering for Startups
You're building fast. Your AI features should keep up. We work with early-stage startups as an end-to-end AI engineering partner — from idea to deployed, without the overhead of an in-house team.
// What we build
Every service is built for speed, reliability, and production-readiness from day one.
Turn complex, multi-step processes into reliable autonomous workflows. Agents that reason, act, and integrate with your systems — not just demo well.
Getting a model to work in a notebook is easy. Keeping it working in production is the hard part. We set up the infra, orchestration, and observability your AI needs to stay running at scale.
Want to add AI to your product but don't have the bandwidth to do it right? We embed with your team to design, build, and ship AI features that are production-ready from day one.
// How we work
Whether you're validating an idea or scaling a product, there's an engagement model built for your stage.
A focused, fixed-scope engagement to take one AI agent, workflow, or feature from zero to production. Fast turnaround, clear deliverables, no fluff.
Ideal for: Pre-seed & seed startups validating an AI bet
End-to-end delivery across the full AI lifecycle. We own architecture, build, and deployment — working tightly with your team throughout. Designed for startups ready to go deep.
Ideal for: Series A startups shipping AI as a core product
A dedicated AI engineering partner as your product scales. Covers new features, infrastructure maintenance, and evolving MLOps needs month over month.
Ideal for: Startups that want continued AI velocity post-launch
// Why startups choose us
Lean engagements designed around startup timelines and budgets. No bloated retainers, no 18-month projects.
From LLM prompting to infra, guardrails, evals, and harnesses, We cover the entire stack. One partner, end to end.
We work autonomously and integrate cleanly with your existing team. You get updates, not requests for direction.
Everything we build is designed to scale — not just demo. Your users will never know the difference between our work and a full in-house team.
// AI by industry
Real project ideas across industries — the kind of things we build every day. Find your sector and see what's possible.
Compress days of manual underwriting into minutes. An autonomous agent pulls credit signals, runs your scoring logic, and writes a structured rationale — flagging only true edge cases for human review.
A production-grade inference pipeline that scores every transaction in real time — with drift monitoring, automated retraining, and full observability so your model stays sharp as fraud patterns evolve.
Turn a wall of numbers into plain-language explanations. An in-app AI that surfaces what changed, what it means, and what to consider — reducing support tickets and driving weekly active usage.
Go beyond difficulty adjustments. An agent that understands where a student is genuinely stuck and why — then generates exercises, worked examples, and pacing changes that actually move them forward.
Deliver structured, rubric-aligned feedback in minutes instead of days. Educators spend their time on the feedback that actually requires their expertise — the AI handles the first pass at scale.
EdTech content goes stale fast. An automated pipeline that monitors your course library, flags outdated material, and keeps your RAG search index current — so learners always get accurate content.
Replace keyword search with genuine intent understanding. An agent that navigates your catalogue conversationally — handling budget constraints, occasions, and objections — and guides users straight to checkout.
Handle the routine, escalate the exceptions. A returns agent that classifies reasons, validates policy eligibility, resolves cases, and triggers logistics — without a human touch for the majority of requests.
Stop leaving margin on the table. An AI feature that monitors competitor prices and demand signals continuously, surfacing price adjustment recommendations within your guardrails — so your team approves, not researches.
SDRs should be having conversations, not doing research. An agent that monitors ICP signals, researches prospects, and drafts personalised outbound sequences — so your team reviews and sends, not starts from scratch.
Tier 1 support is repetitive by design. Train an agent on your docs, past tickets, and resolution patterns — it auto-resolves the majority and drafts responses for the rest, so your team focuses on what matters.
Your product generates signals your CS team never sees. An in-product AI that surfaces churn risk, feature adoption gaps, and expansion opportunities in plain language — so your team acts on data instead of dashboards.
Static route plans break down by mid-morning. An agent that replans dynamically throughout the day — accounting for traffic, vehicle capacity, and SLA constraints — so your dispatch team manages exceptions, not spreadsheets.
Overstock and stockouts are both expensive. An MLOps system that trains per-SKU forecasting models, serves them via API to your procurement system, and auto-retrains as your business changes.
Logistics runs on paperwork. An agent that reads shipping documents, bills of lading, and customs declarations — extracts structured data and writes it to your ERP — so your operations team handles exceptions, not data entry.
Junior associates shouldn't start at the reading layer. An agent that does the first-pass contract review — comparing clause-by-clause against your playbook, flagging deviations with risk ratings, so lawyers start at analysis.
Legal research is retrieval and summarisation, not reasoning. A RAG pipeline over your matter history and precedent library that lets lawyers query in natural language and get cited answers in seconds, not hours.
Most legal drafting starts with boilerplate. An agent that generates NDAs, service agreements, and engagement letters from a structured intake form — in your house style — so lawyers go straight to review and customisation.
Most government helpline queries are routine. A conversational agent that handles eligibility checks, application status, and document requirements — across web and phone — in multiple languages, freeing officers for complex casework.
Policy officers shouldn't spend hours searching dense circulars for a single answer. A RAG-powered internal tool that indexes your entire policy corpus — returning cited answers in seconds, with access controls per department.
Welfare disbursements and infrastructure projects generate enormous data that mostly sits in silos. An anomaly detection pipeline that flags irregularities in near real-time — before they become audit findings or headlines.
// Tools
Pick a model, set your token volumes and request frequency — see your monthly spend update in real time across every major provider.
Select a model
Set your usage
All models — ranked by cost
Prices are indicative and subject to change. Always verify with provider pricing pages.
We'd love to hear about it. Book a free 30-minute call and let's figure out what we can build together — fast.