SOLUTIONS

SAAS COMPANIES

AI features. Dedicated teams. Faster shipping. No lock-in.

Your SaaS product is good.Make it AI-native.Senior engineers, production-grade AI, 30-day terms.

We embed AI features in your product, extend your engineering team with senior capacity, and clear the technical debt slowing every sprint down. Fixed scope or rolling monthly. No six-month minimums.

See the 4 pillars↓

20+

SaaS products shipped

4–8 weeks

first AI feature live

avg velocity lift

4×

cheaper than US headcount

What's actually slowing you down

You're not behind because the product is bad.
You're behind because the engineering capacity isn't there.

ISSUE · 01

Competitors shipping AI, you're not

Your roadmap has an AI feature. It has been there for two quarters. Nobody on the team has shipped a production LLM integration before, and hiring an ML engineer is a 6-month search with a $200K price tag.

ISSUE · 02

Velocity dropped when scale went up

The codebase that worked at 500 users is now a liability at 50,000. Every sprint ships less than the last. Refactors get deprioritized. Engineers are frustrated. Customers are waiting.

ISSUE · 03

Hiring is broken

You posted the senior engineer role three months ago. The pipeline is weak, the good candidates ghost after the first call, and every week the seat is empty is a week of deferred roadmap.

ISSUE · 04

Technical debt owns the roadmap

A third of every sprint goes to bugs that keep coming back. The architecture decisions from year one are now anchors. Your team is fighting the codebase instead of building the product.

ISSUE · 05

AI feature flopped in production

You shipped something. It hallucinated. Customers complained. The team didn't have the eval framework, the guardrails, or the grounding layer to make it trustworthy. It got quietly turned off.

ISSUE · 06

You scaled the team, not the output

You went from 3 engineers to 9 and shipped no faster. Coordination overhead consumed the capacity gain. The answer is not more headcount, it is better-structured capacity.

TODAY

Growing fast. Shipping slow.

01AI feature in the roadmap for 6 months, still a Figma frame

02Senior engineer seat open, no hire in sight at $180K+ ask

0340% of sprints absorbed by regressions and tech debt fires

04LLM prototype built, hallucinating in staging, never shipped

05Velocity flat despite headcount doubling in 18 months

06Competitors announced AI copilot; you have a slide about it

WITH EMULSION

Same team. 3x the output.

01RAG feature or AI copilot live in product within 4–8 weeks, with evals

022–4 dedicated engineers on 30-day terms, no 6-month search

03Sprint output 2–3x higher within 60 days of team embed

04LLM integration with guardrails, grounding, and monitoring in prod

05Architecture cleaned up and documented, new features ship predictably

06AI roadmap executed quarter by quarter, not deferred to next year

Pillar 1 of 4

AI Feature Engineering — embedded in your product, not bolted on

We design, build, and ship the AI features your product roadmap has been waiting on. RAG pipelines, agentic workflows, AI copilots, voice agents. Production-grade with evals, guardrails, and monitoring from day one.

RAG Pipeline & Knowledge Layer

Retrieval-augmented generation over your product data, support history, or docs. Proper chunking, vector store choice (Pinecone, pgvector, Weaviate), hybrid search, and evaluation so every answer traces back to your data, not a hallucination.

$12K–$35K project

Production-accurate. Not a chatbot demo.

View service

AI Copilot & In-Product Assist

Contextual AI assist embedded directly in your product UI. It understands the user's current state, their data, and their workflow, and ships as a feature your customers pay for — not a support shortcut bolted onto the sidebar.

$15K–$40K project

Becomes a retention driver, not a gimmick.

Agentic Workflows & Automation

Multi-step agents that trigger real actions inside your product: CRM writes, notifications, data transforms, approval flows, document generation. Built with guardrails and audit logging so nothing runs unchecked in production.

4–12 weeks delivery

Automates real workflows, not just the report.

View service

LLM Eval & Reliability Layer

If you shipped an AI feature that hallucinated, drifted, or had to be quietly turned off, we rebuild the eval framework, grounding layer, and monitoring around it so it ships reliably in production the second time, not just the first flashy demo.

$8K–$20K project

AI you can actually put in front of customers.

Not sure where to start?

Book a free 30-minute call. We will map your specific bottleneck, whether that is AI shipping delay, velocity drag, or a headcount gap, walk through what we find, and tell you exactly how we would fix it, no pitch attached.

Free · 30-min call

No pitch. No pressure. Just a clear plan.

Book a discovery call

Pillar 2 of 4

Dedicated Engineering Team — your team's capacity, extended on 30-day terms

2–4 senior engineers embedded in your sprint cadence. They show up in your Linear, Slack, and standups every week. PM, QA, and DevOps included. Cancel with 30 days notice. No 6-month recruiting cycle.

Sprint-Embedded Senior Engineers

Engineers who join your rituals, not a separate offshore team you manage. Weekly sprints, shared board, direct Slack access. Assigned, not rotated, so context stays inside the team and velocity compounds sprint over sprint.

$10K–$22K/mo

Feels like in-house. Costs like a contractor.

View service

PM, QA & DevOps Coverage

Every retainer includes project management, QA testing on each release, and infrastructure ownership. Nothing ships untested, nothing breaks without being caught, and you don't need to hire separate headcount for any of it.

Included in retainer

Full-stack capacity, not just IC engineers.

30-Day Cancellation

We earn the engagement every month. No 6-month minimum, no exit fees, no equity asks. If the team is not delivering, you walk with 30 days notice. That accountability is structural, built into the contract, not a promise.

Month-to-month

You are never locked in.

Not sure where to start?

Free · 30-min call

No pitch. No pressure. Just a clear plan.

Book a discovery call

Pillar 3 of 4

Staff Augmentation — senior ICs in your stack, from week one

Single senior engineers dropped into your team for a quarter or more. Full-stack, backend, AI/ML, or mobile. They know your stack, they know your domain, and they ship independently from week one.

Senior Individual Contributors

Engineers with 5–10 years of production experience, placed directly in your team. We match on stack, domain, and timezone, then step back — you interview them, you run the work, and we handle the contract and compliance.

$6K–$12K/mo per engineer

Cheaper than a hire, faster than recruiting.

AI/ML Specialist Placement

Engineers who have shipped production LLM features, fine-tuned models, or built ML pipelines end to end. Not generalists who read the docs last week — engineers who have the scars from running it in front of real users.

$9K–$16K/mo

No ramp-up on AI fundamentals.

Backfill & Surge Capacity

Parental leave cover, acquisition diligence crunch, product launch sprint. We place a senior engineer in a specific role for a defined period and remove them cleanly the moment the need ends, no offboarding drama.

1–6 month engagements

Right-sized. No permanent headcount added.

Not sure where to start?

Free · 30-min call

No pitch. No pressure. Just a clear plan.

Book a discovery call

Pillar 4 of 4

Architecture & Velocity — pay down the debt that is eating your roadmap

If technical debt has turned 40% of every sprint into firefighting, we audit, document, and refactor the parts that are costing you the most velocity. Your team ships faster. Your engineers stop leaving.

Velocity Audit & Debt Map

We analyse your last 12 sprints, your codebase churn patterns, and your error logs to identify the exact debt items costing you the most output. You get a prioritized fix list with ROI estimates attached, not a theory.

$6K–$14K project

You know exactly what to fix first.

Targeted Refactor & Documentation

We refactor the modules with the highest drag on velocity, add tests to the paths that break most often, and document the architecture so new engineers don't spend three weeks just getting oriented before shipping anything.

$12K–$30K project

New features ship faster within 60 days.

Scalability & Infra Upgrade

Database schema redesign, caching layer, queue architecture, CDN and edge config. We handle the infrastructure work that needs to happen before you can safely add the next 10x of users without a rewrite down the line.

Scoped per project

Scales to the next 10x without a rewrite.

Not sure where to start?

Free · 30-min call

No pitch. No pressure. Just a clear plan.

Book a discovery call

Fit

Who this is for

Company size10–200 employees

StageSeries A · Series B · Growth · Profitable

GeographyUS · UK · EU · Canada · Australia

You're running a SaaS product with real customers and real revenue. Your engineering capacity is either too small, too slow, or missing the AI skillset to keep up with where the market is moving.

You don't need another headcount approved by the board.

You need senior capacity on 30-day terms that shows up in your sprint tomorrow.

You don't need a six-month ML hiring search.

You need the AI feature shipped in the next quarter, with evals, not a demo.

You don't need another internal project to clean up tech debt.

You need an external team to pay it down while your engineers keep shipping.

SaaS products we've built and extended

Real products. Real engineers. Real results.

AI / Creative SaaS

Artis

0 → 1

Full product build

AI creative support platform that analyses an artist's style and delivers tailored advice and marketing strategies. Built end-to-end, from AI pipeline to product UI.

View case study

Media / SaaS

Podcast Beacon

Zero to SaaS

Full launch

Podcast discovery platform built from the ground up. Data pipeline, recommendation engine, and subscriber features shipped in a single sprint cycle.

View case study

Security / SaaS

BambooVPN

10K+

Active users

Consumer VPN app with custom protocol implementation, subscription billing, and cross-platform client. Engineering team provided end-to-end.

View case study

AI / Marketing SaaS

ContentCompass

3 AI tools

Shipped to prod

AI content strategy platform with multi-model pipeline, semantic search, and automated brief generation. RAG-powered and production-evaluated.

View case study

Next step

Ship the AI feature your
roadmap has been waiting on.

30 minutes. No pitch. No pressure. We map your specific bottleneck and tell you exactly what it would take to fix it this quarter.

View all solutions

Your SaaS product is good.Make it AI-native.Senior engineers, production-grade AI, 30-day terms.

You're not behind because the product is bad.You're behind because the engineering capacity isn't there.

Competitors shipping AI, you're not

Velocity dropped when scale went up

Hiring is broken

Technical debt owns the roadmap

AI feature flopped in production

You scaled the team, not the output

Growing fast. Shipping slow.

Same team. 3x the output.

AI Feature Engineering — embedded in your product, not bolted on

RAG Pipeline & Knowledge Layer

AI Copilot & In-Product Assist

Agentic Workflows & Automation

LLM Eval & Reliability Layer

Not sure where to start?

Dedicated Engineering Team — your team's capacity, extended on 30-day terms

Sprint-Embedded Senior Engineers

PM, QA & DevOps Coverage

30-Day Cancellation

Not sure where to start?

Staff Augmentation — senior ICs in your stack, from week one

Senior Individual Contributors

AI/ML Specialist Placement

Backfill & Surge Capacity

Not sure where to start?

Architecture & Velocity — pay down the debt that is eating your roadmap

Velocity Audit & Debt Map

Targeted Refactor & Documentation

Scalability & Infra Upgrade

Not sure where to start?

Who this is for

Real products. Real engineers. Real results.

Artis

Podcast Beacon

BambooVPN

ContentCompass

Ship the AI feature yourroadmap has been waiting on.

You're not behind because the product is bad.
You're behind because the engineering capacity isn't there.

Ship the AI feature your
roadmap has been waiting on.