Innovution
Service · Applied AI

Applied AI strategy and development — from opportunity map to production.

Most organizations know AI should be part of how they work. The hard part is getting from that knowledge to something that actually works in production — not just in a demo.

Engagement
Fixed scope · embedded
Outcome
AI system in production
Posture
Human-in-the-loop · secure-by-default
WHAT THIS IS

We help you identify the two or three AI opportunities that actually move the business — then we build them with you. The output is a working system, in your environment, with a human review path your team can defend in an audit.

Every engagement starts with an opportunity assessment — a structured read of where AI moves the needle in your business, ranked by impact, risk, and time-to-value. From there we scope a 4–8 week build window with a single named outcome.

What we build

Patterns we ship most often. Each is real, scoped, and instrumented.

RAG knowledge assistants

Grounded retrieval over your real corpus. Citations, guardrails, evaluation harness, and a defined human review path before any external action.

Agentic workflows

Multi-step automation with explicit checkpoints, tool boundaries, and a recovery story when a step fails. No untethered agents.

Structured generation

Proposal drafts, compliance evidence, technical documents — generated in your schema, in your voice, flagged for review where it matters.

Decision support

Surface the right information at the right step. Not "ask the AI" — context-aware prompts wired into the operator's actual workflow.

How a RAG query actually runs

Retrieval-augmented generation — in plain steps.

A user question becomes an embedding, the embedding hits a vector index over your documents, the top results become context for the model, and the model answers — with citations and a human-review path where the stakes warrant it.

RAG-QUERY · TRACE● live
1
user query
"How long is the renewal grace period?"
…
2
embedding
text-embedding-3 · 1536 dim
3
vector search
top_k=8 · cosine · 142ms
4
context retrieval
6 grounded chunks · cited
5
LLM response
grounded answer + sources
↳ Total trace: 380ms · grounded · 6 citations
Frequently asked

Questions buyers ask before they pick up the phone.

You're ready when there is a defined business workflow with measurable throughput, a clean enough source of truth to ground a model against, and a human owner who will be accountable for the output. If any of those three is missing, the right first step is to fix that — not to start an AI project.
Strategy decides which two or three opportunities to chase, in what order, against what risk. Implementation is the actual build — data pipelines, retrieval, evaluation, human review, integration. We do both, and we never separate them: the strategy work is shaped by what we know is buildable in the time you have.
A system other people can rely on without you babysitting it. That means: observability on every step, evaluation harness that runs on a known set, defined human review for edge cases, rollback path, and a documented owner. A demo answers a question. A production system answers a thousand and tells you when it shouldn't.
A first pilot is 4–8 weeks from a signed scope to something running in your environment. A fuller transformation arc — multiple workflows, multiple teams — is a multi-quarter engagement with embedded delivery leadership, sized to the work.
Yes. The work is rarely held back by technical complexity; it is usually held back by getting clarity on the workflow and the human review boundaries. We sit with the people doing the work, write down what they actually do, and design the system around them — not around the model.
Related packaged offers
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2 weeks · From $22k

AI Opportunity Assessment

A structured read of where AI moves the needle in your business — and where it does not. You leave with a ranked opportunity map and an honest scope.

4 weeks · From $38k

RAG / Knowledge Pilot

A grounded knowledge assistant on your real corpus — with citations, guardrails, and a defined human review path. Not a demo.

6 weeks · From $65k

AI MVP Blueprint

From thesis to a working MVP. Product definition, architecture, the first build, and a path to the next 90 days.

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Workflow & Operations Modernization

Quote-to-cash, renewals, proposal generation, compliance evidence — measured workflow throughput, not slides.

Cloud, Data & Integration

FedRAMP-aligned cloud architecture, data pipelines, and integration with Salesforce, SAP, ServiceNow, and GCP-native services.

Product Strategy & Platform Build

From a market thesis to a working MVP. We define what to build, then build it — with you in the room, not on the sidelines.

Solutions Beyond Ordinary

Bring the work. We'll bring the build team.

Half an hour with our team. We'll either tell you we can help or point you to who can. Either outcome is faster than another deck.