Custom AI, automated workflows, private models and practical advice. Start with the problem; we build the right solution around it.
For decision makers improving a costly process, and teams evaluating a delivery partner. Building your own venture? Explore Builders.
Start from your need: Custom AI development · AI document processing · Insurance
A custom AI build is a model or agent designed for one job in your business, trained or fine-tuned on your data, and measured against a definition of done agreed before the build starts. It runs inside your systems and your team operates it.
Ideolyst · Build 001 · Live
AI workflow automation takes a process your team already runs and already budgets for, and runs it with fewer hands and fewer errors, without replacing the systems it lives in. Agents handle the repetitive and judgment-heavy steps; people keep the decisions that need them.
Ideolyst · Build 002 · Live
On-premise AI deployment runs fine-tuned models entirely inside your own infrastructure or private cloud. No data leaves your perimeter, there is no third-party API in the loop, and the model weights are yours to reuse across future projects.
Ideolyst · Build 003 · Live
AI consultancy at Ideolyst is a fixed-fee, one-to-two-week process mapping that tells you where AI genuinely fits in your operation, where it does not, and what the first build should be. You get a written map, use cases ranked by return, and a quote. You can take it to anyone.
Where AI does not fit, we say so in writing. That judgment is the first thing we deliver.
Ideolyst · Build 001 · Live
Some problems repeat across clients, so we package them as engines you deploy in your VPC or on-prem and pay for by volume. Real-time invoice parsing and validation for supply-chain finance: varied invoice layouts and handwritten tier-3 bills, three-way PO/GRN/invoice match, duplicate and tamper checks, sub-second against 30 seconds to 3 minutes for legacy async queues, 50–60% lower cost per invoice than template OCR (benchmarked on representative sets). Bank-statement analysis for underwriting as a companion.
Proof of value on your own documents in under a day → pilot weeks 1–4 → production weeks 4–8 → scale with volume-tiered, pay-per-use minimums.
For hospital outpatient departments we bring a service-design framework: multi-channel access, live queue with position and time, AI scribe, 12+ Indic languages, HL7/FHIR connectors, on-prem or government cloud. Its figures are benchmarks from published literature, labelled as such, until a hospital runs it.
Typically about three months from the start of Advise, depending on scope and data readiness. Advise takes one to two weeks, Prove three to four weeks, and Go live about two months.
01
1–2 weeks
Use cases ranked by return, scope fixed in writing
Fixed fee
02
3–4 weeks
A working proof of concept on your data, weekly demos
Fixed fee
03
~2 months
In production, on your infrastructure, your team trained
Fixed fee
04
6 months
Six months included: defects fixed at no cost; changes and new scope are quoted.
Included
05
ongoing
Optional retainer for monitoring and new processes
Monthly retainer
Six months included: defects fixed at no cost; changes and new scope are quoted. Full documentation and training at handover.
The person who scopes it signs it off.
Custom-build code, the weights we train for you and your data are handed over in your repositories. Packaged engines are priced by usage; confirm their deliverables and terms separately.
Each phase is quoted after we understand the workflow, data, integrations and deployment needs. Packaged engines use volume-based pricing.
What would you want live in three months?
Every model we deliver comes with an evaluation set, a trace of every decision, and alerting, so your team can see when it drifts. We are packaging this layer as a product; it is currently in build.
Deployment inside your perimeter, PII masked before any model, internal VAPT before go-live, NDAs as standard. No certification is claimed.
Typically about three months from the start of Advise, depending on scope and data readiness: Advise one to two weeks; Prove three to four weeks; Go live about two months.
No. We build and deploy inside your infrastructure.
For custom builds, the code, the weights we train for you and your data are handed over to your team. Packaged engines use volume-based pricing; confirm their deliverables and usage terms when scoping the engagement.
We tell you in the advisory report and you pay only that fee.
The six builds published here span insurance, logistics, e-commerce, investment research and consumer-services marketplaces; the wider 18+ solutions span five industries.
Six months included: defects fixed at no cost; changes and new scope are quoted. Documentation and training are included. A retainer after that is optional.
Last reviewed 2026-10-24