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AI Systems Division

AI that moves through your business.

We build AI systems that retrieve, reason, act, verify, and report. Agents, local RAG, document intelligence, voice control, model routing, evaluations, and workflow automation designed as infrastructure, not a toy demo.

Start an AI build NeuroForge AI app
context
Private knowledge loadedDocuments, databases, user state, permissions, and business rules enter the system.
reason
Model route selectedFast model, frontier model, vision model, or local model based on the job.
tool
Action preparedAPI call, report, dashboard update, workflow trigger, or draft for human approval.
system.status: grounded // tool_access: bounded // audit_log: active // hallucination_budget: zero
Cognitive architecture

The system thinks in stages.

Input is interpreted, context is retrieved, the right model is chosen, tools are called, and output is validated before it reaches a user or changes a system. The intelligence is in the whole loop, not just the model name.

intent parse
context bind
tool decision
verified output
Agents

Autonomy with control points.

We design agents that can observe, plan, use tools, verify results, and stop for approval when the stakes require it. Useful agents are not chaotic. They are bounded systems with memory, tools, and logs.

01ObserveRead the situation.
02PlanChoose the next move.
03ActUse approved tools.
04VerifyCheck the result.
RAG and document intelligence

Answers should carry evidence.

We build private knowledge systems for PDFs, scans, SOPs, contracts, tickets, research, compliance archives, and operational data. The AI can answer questions, compare sources, summarize findings, and show where the answer came from.

ingest: document batches, scans, tables, metadata, permission boundaries
index: embeddings, entities, rejection codes, dates, semantic chunks
retrieve: filtered source passages, citations, confidence, audit trace
answer: grounded response, summary, comparison, export-ready report
Model routing

One provider is not a strategy.

Some work needs frontier reasoning. Some needs speed. Some needs vision. Some needs local deployment. We route by quality, latency, privacy, cost, and task type so the system spends intelligence where it matters.

classify
fast
reason
frontier
vision
multi
private
local
batch
cheap
review
safe
Evaluation and governance

Trust is measured while the system runs.

We add prompt tests, structured output validation, source checks, moderation, usage tracking, cost visibility, fallback behavior, and human review. AI becomes inspectable instead of mysterious.

Control ledger runtime checks
source
GroundingAnswers must connect to approved context and citations.
active
shape
Schema validationStructured outputs are checked before workflows consume them.
enforced
tools
Action boundaryHigh-impact operations require permission or human review.
bounded
cost
Usage traceLatency, tokens, provider spend, failures, and fallbacks are visible.
logged
release.condition: prompt_tests_pass && citations_present && tool_scope_valid && review_gate_clear
Final prompt

Bring the AI idea. We will turn it into a system.

Agents, local RAG, document intelligence, AI dashboards, workflow automation, model routing, voice control, evaluations, and tool-using systems built with real engineering discipline.