AI Use Case Discovery
A written brief of the use case, the data, the model and the expected ROI.
AI Development
Custom AI SolutionsAI Built for the Problem You Have.
Custom AI solutions for problems that no off-the-shelf product fits — a model, a data pipeline, an evaluation suite and a UX shaped to the business outcome, owned by you, designed to be extended by your team, and shipped to production with the guardrails the use case needs.
10+Years Experience
100+Projects Delivered
50+Expert Developers
20+Industries Served
AI Use Case Discovery
Custom Model Build
Data Pipeline & RAG
Evaluation & Guardrails
AI UX & Integration
Production & Operate
Overview
A custom AI solution is the system around the model
A custom AI solution is not "we used GPT". It is a system that solves a business problem, with the model as one component, the data as the fuel, the evaluation as the safety net, and the UX as the surface the user touches. The system is the deliverable, not the prompt.
We build custom AI solutions against a written brief, with the model selection, the data pipeline, the evaluation suite, the guardrails and the UX designed against the business outcome. The output is a system that ships, runs and improves — not a model call that lives in a notebook.
This is the wrong engagement if a SaaS AI product already fits the problem. The cheapest custom AI is the one you do not have to build. We will say so on the call.
- Shaped to the Outcome — The AI is shaped to the business outcome, not the other way round.
- Owned by You — Repos, data, models and accounts in your name from the first commit.
- Evaluated, Not Vibes — An evaluation suite that runs on every change, with the regressions caught early.
- Cost-Defensible — Token budgets, caching and the cost review that keeps the bill honest.
What we deliver
Everything included in our custom ai solutions
Custom Model Build
A model trained, fine-tuned or composed against the data the business owns.
Data Pipeline & RAG
The data ingestion, the chunking, the embeddings and the retrieval the AI needs.
Evaluation & Guardrails
An evaluation suite, the guardrails and the observability the use case needs.
AI UX & Integration
The UX that surfaces the AI, the integration with the systems the user already runs.
Production & Operate
The production deploy, the monitoring, the cost review and the model swap path.
Our process
A proven process for successful delivery
01
Discover
We agree the use case, the data, the model and the architecture on paper.
02
Plan & Design
We design the system, the data pipeline, the UX and the evaluation suite.
03
Develop
We build in two-week sprints with a working slice every Friday.
04
Deploy
We ship to production with the evaluations, the guardrails and the observability live.
05
Optimize & Grow
We read the data, the cost and the evaluations, and ship the next iteration.
Technology
Built with a stack that stays maintainable
Models
- OpenAI
- Anthropic
- Google Gemini
- Open source LLMs
- Custom fine-tunes
Backend
- Python
- Node.js
- LangChain
- LlamaIndex
Data & Retrieval
- Pinecone
- Weaviate
- pgvector
- PostgreSQL
Observability
- LangSmith
- Helicone
- OpenTelemetry
What you can expect
- To First Production Release
- 8-14 wksTo First Production Release
- Target Uptime
- 99.9%Target Uptime
- Evaluations on Every Change
- 100%Evaluations on Every Change
- Agnostic Architecture
- ModelAgnostic Architecture
Industries we serve
Delivered for teams in your sector
A SaaS AI product fits 80% of the use case out of the box, with the remaining 20% accommodated by configuration. A custom AI solution is built for the use case that no SaaS product fits — the data is sensitive, the workflow is unique, the compliance posture is non-standard, or the differentiation IS the AI. We will say so on the call.
A short discovery on the use case, the data, the workflow and the constraints. Most of the time, the answer is "buy the SaaS product, customise the last 20%". When the answer is "build", we will say so and write the brief. When the answer is "buy", we will say so and recommend the product.
The data is the fuel. We start with a data audit, identify the gaps, and design the data pipeline against the use case. The pipeline is observable, idempotent and recoverable. For sensitive data, the pipeline runs on your infrastructure, not a third-party service.
Against the business outcome and the evaluation suite. The business outcome is the metric the business cares about (revenue, cost, time, accuracy). The evaluation suite is the technical metric the team can act on. The two are tied together in the monthly review.
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ERP, CRM, HRMS & custom software we build
Ready to start your custom ai solutions project?Let’s scope it together.
Tell us the outcome you need. We’ll come back with an approach, a timeline and a written estimate.