Custom AI Solutions and Development Services
What are custom AI solutions?
Custom AI solutions are production systems built to solve one specific business problem, using the data, rules, and platforms that already run your organization. That is the opposite of a generic seat license. Off-the-shelf assistants like ChatGPT Enterprise and Microsoft Copilot are general-purpose tools priced per user, and they only see whatever text a person pastes into them. A custom AI system reads directly from the loan origination platform, the EHR, the project management tool, or the student information system, follows the compliance rules your team has written, and returns an answer the business can act on without a human retyping the result.
For a credit union with three developers, a legacy core, and NCUA obligations, that difference is the whole game. A packaged tool cannot see the member data it needs, cannot enforce the audit trail examiners will ask for, and cannot run without a person driving it. A custom system can.
When does custom AI development make sense?
Three conditions usually justify the investment:
- The workflow you want to improve runs at least a few hundred times per month, so automation compounds.
- Off-the-shelf tools cannot see the data required to answer the question well: regulated data, on-premise systems, or internal knowledge bases.
- A wrong answer has a real cost (a denied loan, a missed diagnosis, a change order dispute) that justifies engineering guardrails around it.
If two of the three apply, custom AI development usually pays back inside a year. If only one applies, we recommend a subscription and no project.
What we build
AI copilots for internal teams. Retrieval systems grounded in your policies, procedures, and historical work product, so member service reps, loan officers, project managers, or advisors get accurate answers pulled from your documents instead of guesses. Every answer cites the source document by name.
Machine learning models on your data. Fraud scoring, delinquency prediction, patient no-show forecasting, bid-margin models, enrollment yield models. Trained on your history, monitored in production, retrained on a schedule.
Generative AI and custom LLM builds. Private, policy-grounded assistants that draft correspondence, summarize records, and answer employee questions using your knowledge base. See our Custom GPT and LLM solutions page for the LLM-specific offering.
Document AI and intake automation. Loan applications, prior-auth forms, RFPs, invoices, and transcripts extracted into structured fields with confidence scores, plus human review queues for anything below threshold.
Integrations to core systems. Symitar, Corelation, Epic, Cerner, Procore, Deltek, Workday, Ellucian Banner, Salesforce, and the middleware in between. AI without integration is a demo.
Industries we develop custom AI for
- Credit unions on loan processing, fraud, member service, and NCUA-aligned governance. Details on AI consulting for credit unions.
- Healthcare organizations on documentation, prior authorization, and patient flow, with HIPAA-appropriate data handling. Details on healthcare AI consulting.
- AEC firms on bid analysis, submittal review, and project risk scoring. Details on AEC AI consulting.
- Higher education on enrollment, retention, and administrative automation, with FERPA in scope. Details on higher education AI consulting.
How our custom AI development engagement works
Every engagement follows the same phases, priced fixed-fee per phase so you can stop after any of them.
- Assessment (1 to 2 weeks). We interview the people who will use the system, map the workflow, quantify the current cost, and confirm the data is usable. Deliverable: a written scope, price, and expected payback.
- Prototype (2 to 4 weeks). A working system on a subset of real data, evaluated against a labeled test set your team helps build. Deliverable: measured accuracy on your data and a go or no-go decision.
- Production build (4 to 10 weeks). Integration into your systems, security review, monitoring, retraining pipeline, and change management. Deliverable: a running system your team owns.
- Operate and improve (ongoing, optional). Model monitoring, drift alerts, quarterly retraining, and enhancement work. Priced monthly.
Most projects finish phases 1 through 3 in 8 to 16 weeks. Complex integrations across multiple core systems or heavy compliance review run 16 to 24 weeks.
Where custom AI beats off-the-shelf tools
- Accuracy on your data. Retrieval and fine-tuning against your documents typically move accuracy on internal question answering from the 40 to 60 percent range (a generic chatbot with no context) to the 85 to 95 percent range.
- Cost at scale. Per-seat licensing is priced against every employee. A custom AI system runs on infrastructure priced against the workload, so once you cross a few hundred users the math flips.
- Auditability. Every answer traces to source documents, with prompts and outputs logged for compliance review. Packaged tools are a black box to your examiner.
- Data residency. Sensitive workloads can run inside your VPC, in Azure GovCloud, or on-premise. Data never leaves your boundary when that is the requirement.
Frequently asked questions about custom AI solutions
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Ready to scope a specific custom AI project?
A first call is a 30-minute scoping conversation, not a sales pitch. Bring one workflow you want to fix. We will tell you whether a custom AI build is the right answer, what it will cost, and how long it will take.
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