SaaS Products

SaaS products built to sell, not just to demo.

A demo needs one happy path. A product needs tenant isolation, billing that reconciles, onboarding that works without you on the call, and a support story for the day something breaks for one customer and not the others. That gap is where most SaaS builds stall.

Talk to us All services

One deployment multi-tenant

Northwind LtdGrowth · 24 seats

Acme FreightStarter · 6 seats

Harbourside CoScale · 80 seats

Tenant data isolated at the query layer

MRR $0$1,180$2,340$4,700

In one paragraph

AGI Software Solutions builds B2B SaaS products end to end — multi-tenant architecture, subscription billing, self-serve onboarding, usage metering and admin tooling — including the AI features that increasingly decide whether a product looks current. A focused SaaS MVP typically runs $30k–$70k and reaches paying users in 10–16 weeks; production platforms with billing, roles, integrations and reporting run $80k–$200k.

What We Build

The unglamorous parts decide whether it sells.

Founders arrive focused on the core feature, which is right. What kills momentum three months after launch is always the same list: billing edge cases, tenant data leaks, onboarding drop-off and no way to see what customers are doing.

Tenancy

Isolation you can prove

Tenant boundaries enforced in the data layer and tested for, because "we filter by account ID in the query" is one missed clause away from a breach notification.

Revenue

Billing that reconciles

Plans, trials, upgrades, proration and failed payments handled properly, so your revenue reporting and your payment processor agree without a monthly spreadsheet.

Activation

Onboarding without you

Sign-up to first value without a call, because a product that needs a founder on every setup does not scale past the founder.

Visibility

You can see what happens

Product analytics, per-tenant health and error tracking from launch, so churn arrives as a signal you can act on rather than a cancelled subscription.

Plain English

What makes a build a SaaS build?

A SaaS product serves many customers from one deployment, which changes almost every engineering decision. Data has to be isolated per tenant and provably so. Releases have to ship to everyone at once without breaking anyone. Pricing has to be enforced in code. And every customer has to be able to sign up, configure and get value without a human from your team involved.

None of that is visible in a demo, which is why so many products are demoed long before they can be sold. Building it in from the start is considerably cheaper than retrofitting it once you have customers whose data cannot move.

Compared

SaaS MVP vs full product build

Almost every founder should start on the left. The mistake is staying there too long, or skipping it entirely.

	SaaS MVP	Full product build
Goal	Prove someone will pay	Scale what already sells
Tenancy	Isolation done properly from day one	Same, plus per-tenant configuration
Billing	Stripe checkout, one or two plans	Metering, upgrades, proration, dunning, tax
Onboarding	Guided, some manual steps acceptable	Fully self-serve
Timeline	10–16 weeks	5–10 months
Typical cost	$30k–$70k	$80k–$200k

How We Build It

Five stages from problem to production.

The same process on every engineering project, scaled to the size of the problem.

Discovery

We map what the process actually does today, including the parts that live in one person’s head, and what it costs when it goes wrong.

Architecture

Data model, integration points, permissions and hosting decided up front, because these are the choices that are expensive to reverse later.

Build in slices

Working software every couple of weeks, sequenced so the riskiest piece reaches real users first rather than last.

Integrate and harden

Connecting to the systems that hold your data, then security, load and failure testing against realistic volumes instead of demo data.

Handover and support

Documentation, a walkthrough for whoever maintains it, and ongoing support if you want it. The repository is yours either way.

Use Cases

Where SaaS products pay off.

The patterns we see deliver, across startups, SMEs and enterprise teams.

Vertical SaaS

Software for one industry

Deep, opinionated products for a specific trade or sector, where the domain rules are the moat and generic tools have never quite fitted.

AI-native

AI-first products

Products whose core value is a model — with the retrieval, evaluation, cost control and fallback behaviour that keeps unit economics intact at scale.

Internal to product

Productising what you built

The internal tool your customers keep asking to buy, turned into a sellable product with tenancy, billing and onboarding.

Marketplaces

Two-sided platforms

Supply, demand, matching and payments — including the trust, dispute and payout mechanics that decide whether a marketplace holds together.

Tech Stack

What we build on.

Deliberately boring, widely supported technology. The goal is software your team can still hire for in five years.

Front end

React, Next.js and TypeScript, with server rendering where it earns its keep for speed or SEO.

Back end

FastAPI, Django and Node.js. Python where the work touches data or models, TypeScript where it does not.

Data

PostgreSQL as the default, Redis for caching and queues, and a vector store only when retrieval genuinely needs one.

Infrastructure

Docker and Kubernetes on AWS, GCP, Azure or your own servers. Your cloud account, your bill, your control.

Integration

REST and GraphQL APIs, webhooks, message queues and MCP servers for the systems that need to talk to AI.

Quality

Automated tests, CI on every commit, staged deploys and monitoring wired in before launch rather than after the first outage.

Related Work

Systems we have shipped.

AI DevelopmentMarketplace

AI Marketplace Platform

Support chatbot, live SEO analyser and a vector recommendation engine, all sharing one retrieval layer.

+10% GMV, 40% fewer support tickets

AI DevelopmentAI Chatbots

Conversational AI Studio

Context-aware multi-channel chat that qualifies inbound leads and routes them to the right person.

3.2× qualified leads, 54% faster replies

AI DevelopmentComputer Vision

Smart Video Chunker

A pipeline that chunks long-form video into searchable scenes, transcripts and entity timelines.

Under 12ms inference at 30 FPS

See all case studies

What Teams Say

Hear from the teams we work with.

“We needed a voice agent that could actually qualify leads, not a chatbot pretending to be one. The team shipped a sub-700ms pipeline in 6 weeks. It now handles 5k calls a day.”

Priya RajHead of Growth, Ninjatech

“What sold us was their willingness to put AI engineers and product designers on the same call. We got working prototypes by week two and a production rollout in three months.”

James ThorntonCTO, Allindex

“AGI designed a CRM system tailored to our client management process. It is intuitive, reliable, and has centralized all our communication and history in one dashboard. This has greatly improved client retention.”

Carlos MendesProduct Manager, Qilinlab

Common Questions

Before you get in touch.

How much does SaaS development cost?

A focused MVP with real multi-tenancy, Stripe billing and one or two plans runs $30k–$70k. A production platform with usage metering, roles, integrations, admin tooling and reporting runs $80k–$200k. AI features add roughly $10k–$40k depending on whether they need retrieval and evaluation infrastructure.

How long until we can charge customers?

10–16 weeks for an MVP that can genuinely take money — sign-up, subscription, isolated tenant data and the core workflow. We sequence it so the feature you are betting on gets in front of real users first, not last.

Can we start with a single-tenant version and add multi-tenancy later?

You can, and it is usually a false economy. Retrofitting isolation after you have customers means a data migration you cannot get wrong. Building it in at the start costs days; adding it later costs weeks and carries real risk.

Do you handle billing and payments?

Yes — typically Stripe, sometimes Paddle where merchant-of-record handling of global tax is worth the fee. That includes the parts founders underestimate: proration, plan changes, failed-payment recovery and keeping your reporting consistent with the processor.

Will you help after launch?

If you want. Most SaaS clients keep us on for iteration through the first year, because the roadmap that matters is the one written after real customers start using it. Others take it in-house once it is stable. Both work.

Do we own the product?

Entirely. Code, infrastructure, customer data and the Stripe account are yours throughout. We do not take equity, revenue share or hold any part of the stack.