Agents, grounded and under control.
Kineloop is an AI product studio. We build agent-native software that answers from verified context and pauses for a human before it acts. Every product, two commitments: grounding and control.
Grounded, controllable AI across voice, support, developer tooling, and healthcare.
Built in the open. Grounded on real systems, not guesswork.
Technology names are property of their owners. Kineloop is unaffiliated.
The hard part of AI was never capability. It is trust.
Agents are capable now. They still are not trustworthy by default: they hallucinate and act without oversight. Every Kineloop product closes that gap with two commitments, both of which show up as real engineering in every codebase.
Grounding
Agents answer from verified context: versioned graphs, retrieval, trusted sources. Not guesswork.
- Per-turn RAG
- Versioned code graphs
- Source attribution
- Corpus-only answers
Control
Consequential actions are gated: human approval, escalation, policy, fail-closed defaults. Not unchecked.
- Human approval gates
- Confidence escalation
- Policy engine
- Pause by default
Every consequential action pauses for a human.
Threshold intercepts an agent's tool calls, evaluates policy in memory, and routes each one. Unknown or risky actions never auto-run. The default decision is PAUSE.
EXECUTE
known-safe, allowed
PAUSE
human approves via Slack
BLOCK
denied by policy
every decision logged before the response returns
Every product, two commitments.
Vertical SaaS
Agents deployed into a real business workflow.
Open source & Infrastructure
The layer that makes agents safe to run.
HelpNest
Open-source AI support that resolves customer questions and escalates the hard ones.
- RAG over your KB, with citations
- Confidence-scored escalation
Threshold
MCP gateway that gates every agent tool call.
- PAUSE by default on unknowns
- Human approval via Slack
Kine Agent
Local-first desktop orchestrator for coding-agent CLIs.
- Live approve/deny gate for agent tool calls
- Per-session worktree isolation
Developer Tools
Answers grounded in a graph of your work.
We name the mechanism, every time.
No product here is "autonomous and safe by magic." Grounding and control are specific, and you can read them in the code.
The knowledge index is prefetched while the phone is still ringing, so context is in memory before the caller says their first word: no dead air, no cold start. The 1-3 second SIP ring window hides the load, and every turn injects retrieved knowledge with citations.
Answers are retrieved from your knowledge base via embeddings and vector search, and every AI reply cites the articles it used. Grounding you can click.
No matching policy, no matching condition, even an unknown operator: every ambiguous path resolves to PAUSE, never EXECUTE. The fail-safe is structural, not a convention.
Every session runs in its own git worktree on its own agent branch, cut from HEAD. Agents never touch your working copy: you review the diff and decide what merges.
The agent can only reach the graph through typed semantic verbs and a scoped query builder, never raw Cypher. Blueprint validators reject any edge or repo that is not actually in the graph.
The model is constrained to the retrieved graph context: if the answer is not in your papers, it says so instead of improvising. Every answer returns its citations and the exact subgraph it used.
The engineering is the product.
Show the mechanism
We name the retrieval, the graph, the gate, the policy. Never "autonomous and safe by magic."
Order from noise
Raw agent output resolves into reviewable structure, the same way our dither resolves into a loop.
Honest by default
Local-first where it counts, fail-closed on unknowns, limits stated plainly. No overclaiming.
Put agents to work. Keep them in the loop.
Explore what the studio ships, or talk to us about building, partnering, or investing.