Strategy
6 min read
Build vs. buy: when custom software makes sense
Should you build custom software or buy off the shelf? Compare total cost of ownership, license creep, integrations and differentiation, with a checklist.
Read articleAI integration
Put AI to work where it actually saves time
We help businesses find the tasks where AI pays for itself, then build it into the tools your team already uses. We build it with guardrails and testing, and we tell you what it will cost to run.
- How it's priced
- Prototype first
- Timeline
- Prototypes in 2 to 4 weeks, production in 6 to 12
- Where
- Panama City, FL · serving the US
Who it's for
Who we build this for
- Teams buried in documents, emails and data entry
- Product companies adding AI features for their customers
- Leaders who want a realistic AI plan instead of a demo
- Enterprises and regulated businesses with data that must stay private
Problems we solve
What's getting in your way, and how we fix it
Hours lost to repetitive work
We automate reading, sorting, summarizing and drafting, with people reviewing the output where it matters.
Knowledge trapped in documents
We build assistants that answer questions from your own policies, manuals and records, with sources cited.
Pilots that never reach production
We evaluate quality against real examples, add monitoring and ship features your team can rely on.
Worries about data and cost
We use enterprise model providers that don't train on your data, and we design for predictable running costs.
What you get
What's included, in writing
Your proposal lists every deliverable, so you know what you're paying for before we start.
Technology we use
- Claude
- OpenAI
- Amazon Bedrock
- Python
- TypeScript
- PostgreSQL with pgvector
- AWS Lambda
- n8n
- AI opportunity workshop and use-case shortlist
- Prototype tested on your real data
- Retrieval and document processing pipelines
- LLM features built into your product or tools
- Evaluation suite and quality benchmarks
- Guardrails, logging and cost controls
- Workflow automation across your systems
- Team training and documentation
How we work
Four steps from first call to launch
You sign off on scope and price before we start, then see working progress every week.
- Step 1
Discover
We learn your business, users and goals, then agree on scope, budget and what success looks like, in writing.
1 to 2 weeks
- Step 2
Design
We map the user journeys and design the interface, and you sign off on a clickable prototype before production code starts.
1 to 4 weeks
- Step 3
Build
We build in short cycles and give you a live preview link from the first week, so you can watch the software take shape.
3 to 12 weeks
- Step 4
Launch and support
We handle the launch, monitoring and handover, then stay on to host, support and improve what we built if you want us to.
Ongoing
Is our data safe if we use AI?
We use enterprise APIs and cloud services with contractual commitments not to train on your data, and we keep sensitive information inside your own cloud account where possible.
How do you know the AI is giving good answers?
We build an evaluation set from your real examples and measure every change against it. Where accuracy matters, a person reviews the output before it's used.
What does AI cost to run?
It depends on volume and the model used. We estimate running costs during the prototype, so you know what to expect before you go live.
Can AI connect to our existing systems?
Yes. Most of our AI work is integration: connecting models to your CRM, document storage, email or internal databases.
Insights
Further reading
Have a project in mind?
Book a free 30-minute call. We'll talk through what you need, tell you what we'd do and follow up with a written estimate. Prefer email? We reply within one business day.