Seven offerings cover strategy through continuous support so your AI product stays measurable, integrated, and owned after launch.
We built and fine-tuned an LLM assistant on judgments, bare acts, and government policies. Published outcomes include 200+ daily queries handled and research time cut from hours toward minutes, with 10K+ users onboarded on related agent delivery coverage.
200+ daily queries; research hours → minutes; 10K+ users onboarded as published.
We do not sell prototype theater. You get a 40-hour free pilot on one query-success, research-time, or activation KPI, plus eval gates and HITL before high-risk actions write to your systems of record.
You need AI Product Engineering Services that survive production traffic and security review - not a demo lab brochure.
We apply AI Product Engineering Services to domain data and approval rules your buyers already live with - not generic chat wrappers.
You get a scored path from one AI product KPI to a release your team can own - not a vague full-cycle promise.
Pricing stays custom because data, models, and compliance differ. What stays fixed: quality meaning, time-to-start, and a low-risk pilot path. Senior AI/ML and product engineers on your surface - not junior-only fill. A scoped 40-hour free pilot can start after a short discovery call.
Use this when the first AI product slice and acceptance criteria are clear.
Use this when prompts, retrieval, and tools will flex after user feedback.
Use this when you need ongoing AI Product Development ownership across quarters.
These figures come from BigOhTech published pages. We do not invent percentages for this service page.
Use this table when you compare a demo lab, an AI Product Engineering Services partner, or building everything inside.
Pick the engagement shape that matches your stage - greenfield AI product, feature add-on, RAG, agents, or post-launch partnership.
Stack choice follows your data path and which product surface may ship first. We stay on tools BigOhTech already delivers with on AI/ML and agent programs.
AI Product Integration sticks when your models meet the clouds, repos, and business systems your team already runs.
We run AI Product Consulting through Integration so product and engineering leads get a scored pilot and a handoff they can own - not a brochure that promises competitive advantage without eval gates. How far has enterprise spend moved as AI enters day-to-day product and engineering workflows?
Capabilities that make AI Product Engineering Services useful in production - discovery, data readiness, pilots, build, eval, and handoff together.
No. We ground answers with retrieval where possible, add eval suites, and keep humans in the loop on high-risk actions. Teams still approve residual risk explicitly.
AI/ML Development covers broader AI capability builds. This page focuses on product lifecycle - consulting, development, integration, and continuous support for AI-native or AI-augmented products.
Your product IP, data, and repos stay yours under the MSA and SOW. We work under NDA for architecture and data discussions.
We pick one KPI and one slice, wire limited retrieval or agent tools, and score readiness inside about 40 free hours. You decide whether to expand without a long contract first.
We connect model and agent surfaces to CRM, helpdesk, ERP, and internal APIs with auth, logging, and rollback paths. Integration is part of the program - not an afterthought sidecar.
You get pilot-first delivery, eval and HITL on high-risk actions, and custom agency build - not a demo lab or resume-only staffing fill. We run under CMMI Level 3 appraised and ISO 27001 certified process with senior engineers in your tools.
Pricing is custom because data, models, and compliance differ. We share quality meaning, time-to-start, and a model (fixed milestone, time and material, or dedicated team) before you commit.
Typical scope covers AI Product Consulting, AI Product Development, AI Product Integration, RAG or agent builds, eval and security gates, and DevOps handoff. First pilots often own one query-success, research-time, or activation KPI on a thin production slice.
Yes. Agent surfaces pair with AI Agent Development patterns when tool use and multi-step workflows belong on the roadmap - still piloted on one measurable outcome first.
A scoped pilot can start after a short discovery call - often measured in weeks once KPI and data path are clear. Multi-quarter platforms take longer when regulated data and HITL rules are heavy.
Yes. Many buyers combine AI Product Engineering Services with Hire AI/ML Developers when they need capacity inside their own process.
We offer ongoing monitoring, model/prompt updates, and incident support so AI products stay reliable as usage grows. See our IT Support and Maintenance service for post-launch ownership options.
Share your project goals, timeline, and technical requirements. We'll review your requirements and send a tailored solution with an indicative estimate within 48 business hours.
