Custom ops systems for teams outgrowing their tools

We build the software your business runs on, with AI built in from day one. For teams outgrowing spreadsheets, or hitting the ceiling of a low-code and SaaS stack: the integrations that don’t work, the changes that need a contractor, the places AI can’t reach.

Our take
Technology and AI are moving fast.

Software that was the right call a few years ago now quietly locks you out of what comes next. What used to be a stretch to develop is now table stakes for operating a business efficiently.

We build what supports your business.

The internal software your business runs on: project tracking, client records, invoicing, the portal your clients log into. Built on foundations you own, and handed over with your team trained to work with it directly. Not copy-pasting into ChatGPT to find out what the business already knows.

Teams need help finding the leverage.

Most teams know AI is important. Fewer can see where it actually pays back in their specific business, or how to integrate it into the systems they already run. Part of what we deliver is the answer to those two questions: where the leverage is, and how to build it in.

AI is a contributor, not a feature.

If you can't plug an AI tool of your choice into the system and pull info or do work, the system isn't working. We build so the AI tool you reach for can read your records, draft against your playbooks, and write back. The kind your team uses on day one, and keeps using.

Any of this sound familiar? We kept hitting it too.

Stack in Layers
AI On The Side
Slow & Expensive
Change Overhead
Contractor Roster
Platform Ceiling
Per-Seat Pricing

The problem

How we fix it

Your stack grew in layers.

The problem

Airtable, a handful of SaaS tools, Zapier holding it together. Now nobody wants to touch it, because one wrong click breaks three things downstream.

How we fix it

We pull project tracking, client data, and workflows into one system you own. The specialty tools that earn their keep stay. Everything else goes.

AI is something your team uses on the side.

The problem

Your team uses ChatGPT for drafts, Claude for summaries, maybe Copilot in a spreadsheet. None of it knows anything about how your business runs.

How we fix it

AI reads and writes through the system itself. It pulls from your data, answers questions about your clients, drafts against your playbooks. Not a sandbox that forgets context every conversation.

Every change takes weeks and costs more than budgeted.

The problem

You pay a contractor, you wait, you get something close to what you asked for, you iterate, you pay again.

How we fix it

Your team makes day-to-day changes without us: new fields, views, workflow tweaks. Structural changes ship in days instead of months.

Every small ask becomes a project.

The problem

Adding a field, adjusting a workflow, turning on a new feature: each one means a contractor quote, a ticket, a rebuild of half the system, and a two-week wait before anything moves.

How we fix it

Your team owns the small stuff: new fields, new views, workflow tweaks. Same-day changes, no contractor required. We step in for the structural work. Most of the day-to-day stops being an ask.

You're paying five contractors who each see a slice.

The problem

A low-code builder, a Zapier specialist, a spreadsheet wrangler, maybe a fractional analyst. Nobody sees the whole. Your SaaS bill keeps climbing.

How we fix it

One team that sees the whole picture: data model, workflows, AI layer, interface. You stop coordinating contractors and start shipping.

The ceiling is getting lower.

The problem

Record limits. Rate caps. Features gated behind enterprise tiers. Every new capability you want is a pay wall or a wait list.

How we fix it

We build on open infrastructure: Postgres, code you own, AI through models of your choice. You are not subject to the platform's roadmap or tier structure.

Your software bill grows faster than your team.

The problem

Every new hire adds a seat to every tool. Five platforms, ten licenses, a monthly bill that climbs even when the work stays the same. You pay more just for the privilege of having a team.

How we fix it

On your own infrastructure, adding users costs nothing extra. The bill scales with what you build, not with how many people log in. Hire five more people next quarter and your costs look the same.

There’s another way. One system you own, built around how your business works, with AI that can read, draft, and update it the way your team does.

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“You feel like AI should be transforming how the business runs. Instead it’s scratching the surface. Another summary, another tab, another ‘that was kind of useful.’”

What we build.

One system. Built for your business. Owned by you.

One cohesive system in place of scattered tools.

We bring the software your business runs on into one place: project tracking, client data, workflows currently held together by spreadsheets and Zapier. Specialty tools that already work stay put. You end up with one place your team and your AI can both read and write to.

AI wired into your data, not stapled on top.

Your team asks the system for a status summary, a draft invoice memo, or a list of stuck projects. It reads the same records your team does and answers from that, not from a hallucination or a stale export.

One partner instead of a contractor roster.

You pay roughly what you're spending on your current contractor mix, and you get end-to-end visibility. One team sees the same code, the same workflows, the same data. Instead of tickets scattered across specialists who've never met, one partner with context.

Orchestration

Your database, your automations, and your AI finally know about each other. A change in one becomes updates everywhere else.

Reachable by AI

Your records, your workflows, your logic: all exposed to AI in a way a closed platform can’t match.

Ownership

Your code, your data, your infrastructure. No per-seat pricing, no record limits, no vendor surprises.

Speed

Changes that took weeks take days. AI-assisted development moves at your speed, not a platform's roadmap.

No ceiling

No seat limits, no record caps, no rate ceilings. The system grows with the business.

One partner, not five

Breadth, context, and consistency, without the contractor coordination overhead.

Our partners.

The three partners building this with you: an architect, an AI engineer, and an operations lead. Years of building the internal systems teams actually use every day.

Baz Filmer, Founder & Lead Architect at Shawmut AI

Baz Filmer

Founder & Lead Architect

Baz founded Shawmut Consulting after leaving a product role at Whoop. The practice started as a low-code and Airtable agency for founder-led service companies, building internal tools, ops systems, and workflow automation. Watching a client rebuild months of that work in a week using an AI agent made clear the low-code era was closing. That's what Shawmut AI is built around.

Cole Crescas, AI Engineering at Shawmut AI

Cole Crescas

AI Engineering

Cole is an AI engineer on Indeed's internal AI team, where he builds production tooling for a large technical organization. He's hands-on with the infrastructure behind this kind of software: MCP servers, Supabase, Composio, OAuth flows, and the developer stack we use to ship. On Shawmut AI engagements, Cole leads AI integration and technical depth.

Anthon Pavlov, Operations & Delivery at Shawmut AI

Anthon Pavlov

Operations & Delivery

Anthon spent years in corporate operations leadership at a large enterprise, where he ran internal teams, managed vendor relationships, and saw firsthand the gap between what software looks like in a demo and what it has to do when a real team depends on it every day. He brings the operator's perspective to Shawmut AI engagements.

Build with AI, not toward it.

Bolt AI onto an existing system and it has to learn your architecture from the outside. Build the system with AI and it’s been inside the work from day one. No handoff, no ‘please read these docs.’

The Traditional View (How enterprises are still planning for AI)
Data & DatabasesStructure first
Data PipelinesThen connect
AutomationThen automate
AI AgentsThen, maybe, AI
Build up to AI
Humans required at every handoff
Between each layer, someone has to manually pull data out, reshape it, and push it up. AI can't move between layers because nothing was built for that. People end up being the glue, and the bottleneck.
You're "never ready"
The pyramid creates a trap: you can’t get to AI until the layers below are perfect. But they’re never perfect. So AI stays a someday project.
The AI-Native Approach (How small teams are already doing it)
Data & DatabasesAI structures it
Data PipelinesAI connects it
AutomationAI orchestrates it
AI AgentsAI extends it
AI
AI has full context
Because the whole system is built in code AI can read, it understands the full picture. The data model, the business logic, the automation rules, the interfaces. When it makes a change at one layer, it knows what that means for every other layer.
You start with AI, not build toward it
You don’t wait until the foundation is perfect. AI is inside the work from day one: structuring the database, writing the code, running the automations, shipping the features.

Our pricing.

Pricing up front. No lock-in. Every engagement starts with a project build and can continue as a retainer. Either we keep maintaining and evolving your system, or you take ownership outright and we step away. The code and the documentation for how to use it are always yours. We build every system so you could run it without us.

Custom build
The initial build. Scope, design, ship, hand off.
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Included
  • Discovery and system design
  • Data model and integrations
  • Working system in 4–8 weeks (typical)
  • Team training and documentation
  • Launch support
Basic
For teams with a stable system that needs steady maintenance.
$1,500 / month
Included
  • Monitoring, backups, integration health
  • 2–3 hours a month of proactive work
  • Bug fixes and small tweaks absorbed
  • Monthly status email
  • 2-day email response SLA
Still project-scoped: anything more than 2 hours of defined work.
Premium
For teams using us as fractional leadership on their internal software.
$5,000 –$7,500 / month
Everything in Standard, plus
  • 20 hours a month of fractional capacity
  • Monthly strategy session with all three partners
  • Same-day response for urgent items
  • First look at new AI capabilities we develop
  • Medium work absorbed (under 20 hours each)
Still project-scoped: large builds over 40 hours and any dedicated strategy work.

No lock-in past the first year. Month-to-month after that, with 30 days notice.

We build on open infrastructure. Any developer who works in Next.js and Postgres can pick up your system.

Tier review every 6 months. We recommend downgrading if you're under-using. No overpaying for capacity you don't need.

In practice

Frequently Asked Questions

Founder-led and owner-led businesses, typically 5 to 50 people, with revenue coming in and operations starting to feel like the bottleneck. The vertical doesn’t matter much. The shape does.

Initial builds typically run $5K–$15K, depending on scope. They’re usually a focused first project like migrating a base, rebuilding a workflow, or getting your data into a structure your team and AI can both work with. From there, the system grows through retainer work and follow-on projects rather than as one big upfront build. The exact number is locked at the end of the 1–2 week discovery phase, before any build work begins.

No. Most clients start with a focused first project rather than a full rebuild. That might be migrating one base, building a single internal tool, or restructuring data so you can use it. From there, the system grows through follow-on projects and retainer work as the business needs more. You’re not locking into a big upfront engagement to find out if it works.

4–8 weeks end to end, in three phases. Discovery (1–2 weeks): interviews, data audit, written scope, fixed quote. You can stop here if you want. Build: database, automations, AI agents, internal tools. Your team is running live work through it before handoff. Handoff includes training and runbooks. From there: take ownership and run it yourself, or continue on retainer.

Your existing system is the spec. We don’t ask you to rebuild what you already know works. Discovery captures every table, automation, and integration you currently use. The build translates that into a system you own. Your existing setup stays running until cutover, so nothing breaks while we work.

The promise of low-code (Airtable, Softr, Monday) was that anyone could maintain their own system. In practice, once a system gets complex enough, non-technical users stop touching it. The platform that was supposed to put them in control ends up locking them out, because every change feels risky and the entry point is higher than it looks. AI-native systems flip this. Your team describes what they want in plain language (‘add a status field to client records and let me filter by it’), the AI drafts the change, and you or we review before it ships. The result: your team makes more of their own changes than they ever would inside a no-code platform. Bigger structural shifts (new integrations, new AI agents) come back to us, or any developer who works in Next.js and Postgres.

AI in the system means your team can ask things like ‘show me which campaigns are slipping and why,’ ‘draft an invoice memo from last month’s project work,’ or ‘find every conversation with this client that mentioned pricing.’ The AI reads from the same records your team does (not pasted context, not yesterday’s CSV) and answers grounded in what’s actually happening. It can also write back to records when work is done, with you or us reviewing before changes commit.

Everything. The code (as a Git repo we hand over, not a zip), the database (on infrastructure you control), the documentation, and the credentials. Retainers run month to month with 30 days notice. There’s no penalty for leaving. If you walk, we do a clean handoff: docs sync, credential transfer, and a walkthrough for whoever takes over.

Where your data lives depends on your preference. Some clients want it on infrastructure they own and control: typically a Postgres database on Supabase, AWS, or self-hosted, with credentials handed over at handoff. Others, especially in an ongoing retainer relationship, prefer us to host it on our own infrastructure. AI model calls go to providers like OpenAI or Anthropic, and your data isn’t used for training under their API terms. If you have stricter requirements (HIPAA, NDA constraints, specific data residency), we configure for those during discovery.

Yes. Every system we build uses a stack any competent developer can pick up: Next.js, Postgres, and standard tooling. Documentation, runbooks, and the deployment setup are part of every handoff. If you want to bring in your own dev, hire in-house, or move to another firm, the system is ready for it. That’s a deliberate design choice, not a contingency.

Two common paths. Most clients continue on a monthly retainer that covers ongoing maintenance and new builds. Tiers run from steady maintenance through fractional capacity for active development. For clients who don’t want a retainer, we also do ad-hoc projects: scoped, priced, shipped. You can also bring in your own developer or another firm. The system is built to be extended by anyone who works with Next.js and Postgres (part of any competent developer’s repertoire), or by anyone willing to dig in themselves and use AI to draft and troubleshoot the changes.

Talk to us

Pick a time, or send us a question. Either way, we get back to you within 24 hours.