Make AI
simple to execute.
For nearly two decades, Ricochet has turned complex technology into working systems for national labs and science organizations. Now we do the same for AI — grounded in your data, governed for review, and deployed inside your walls.
The AI part is the easy part. Doing it inside a national lab isn't.
See how we workPlenty of teams can wire up a chatbot. Far fewer can do it in an environment with sensitive data, real review processes, and scientists who will not trust an answer they can't verify.
That's the gap we close — vendor-neutral, grounded, and built to clear review.
What we build for
science organizations.
Six areas, from first strategy to running systems. Engage one as a focused project — or sequence them as a roadmap.
AI Opportunity Assessment 5×5 FOR AI
Our intake methodology, pointed at AI: surface the highest-ROI use cases and rule out the hype before a dollar is spent.
Roadmap & Build-vs-Buy
A sequenced plan — what to buy, what to build, what to wait on — scoped to your budget and procurement reality.
Governance & Policy Alignment
Responsible-AI guardrails aligned to DOE's GenAI direction — validation, labeling, human-in-the-loop, audit.
Data-Readiness for AI
Turn scattered documents and systems into an AI-ready, well-governed corpus. Information chaos in; trustworthy foundation out.
Grounded Knowledge Assistants RAG
Assistants over your reports, SOPs, and publications that cite their sources, so scientists can verify every answer.
Legacy & Tacit-Knowledge Capture
Ingest decades of technical reports, lab notebooks, and handwritten notes into a queryable base — addressing brain-drain.
Document Ingestion Pipelines
Production PDF / scan / image → chunk → embed → searchable-KB pipelines, with per-workspace isolation.
Enterprise & Semantic Search
Search across your content and interactions, architected to scale from day-one keyword to full semantic retrieval.
Multi-Agent Orchestration
Expert-panel, review-panel, and structured-debate workflows where grounded agents collaborate — and disagree productively.
Agentic Research Assistants
Goal-driven agents over your corpus plus open databases — arXiv, OSTI, PubMed, OpenAlex — with a human in the loop.
Autonomous & Scheduled Agents
Proactive agents for literature monitoring, compliance reminders, and alert workflows that run on a cadence.
Workflow Automation
Machine-readable AI outputs that plug straight into your existing business logic and systems.
On-Prem / Self-Hosted / Air-Gapped
Run open models on lab-controlled hardware for sensitive or pre-publication data — complementing internal platforms.
Multi-Provider LLM Gateway
One vendor-neutral layer across OpenAI, Anthropic, Gemini, and self-hosted models, with failover and per-workspace selection.
Bring-Your-Own-Key
You own the keys, the data residency, and the costs. We provide the platform; you stay in control of the spend.
Systems & Data Integration
Connect AI to existing lab systems and proprietary data via a plugin / OAuth architecture — no forking your core tools.
Audit Trail & Traceability
Full, encrypted logging of every prompt, response, token count, and cost — queryable for compliance and review.
Cost Governance & Metering
Usage caps, budgets, and chargeback across teams and divisions, so AI spend stays visible and allocated.
Content Safety & Guardrails
Pre-inference moderation and prompt-injection defenses — out-of-policy content blocked before it reaches the model.
Evaluation & Accuracy Testing
Eval harnesses and anti-hallucination checks so you can trust — and demonstrate — that a system performs as claimed.
Custom AI Apps & Copilots
Purpose-built apps: multi-persona advisory panels, onboarding copilots, safety and compliance assistants, proposal tools.
Multimodal & Voice AI
Document and vision AI, plus text-to-speech for accessible, audio-delivered training and outreach.
Rapid AI Prototyping 30-DAY
A working, demo-able prototype fast — mirroring our track record of getting initiatives underway in under 30 days.
Enablement & Training
Prompt-engineering workshops and adoption programs that turn non-technical staff into AI-assisted researchers.
To pressure-test every layer of the modern enterprise-AI stack, our team built a complete platform end to end. Not a diagram — a working system.
Every capability on this page — proven in one system.
Multi-model gateway, governed memory, multi-agent orchestration, compliance gates, full audit logging, and multimodal output — designed, built, and operated in-house.
Retrieval & knowledge
Tenant-isolated semantic retrieval with source-grounding and an ingestion pipeline for documents and scans.
Multi-agent orchestration
A meta-agent that routes which expert responds, when, and how long — including a productive debate mode.
Gateway + BYOK
OpenAI, Anthropic, Gemini, or self-hosted — with per-workspace model selection and customer-owned keys.
Governance & observability
Encrypted audit logging of every call, token-and-cost metering, and a pre-inference content-safety gate.
Governed memory
Policy-controlled extraction of durable facts and rolling summarization — long context at predictable cost.
Multimodal & voice
PDF and image understanding, handwritten-note OCR, and streamed text-to-speech output.
Six reasons labs trust us with it.
Science-native
We already speak national lab. Two decades inside this world means you don't spend the first month explaining your environment to us.
Your data stays yours
Bring-your-own-key, vendor-neutral, deployable on lab-controlled or air-gapped infrastructure. Your keys, residency, and spend.
Grounded, not guessing
Retrieval with citations, so every answer traces back to a real source. A confident wrong answer is worse than none.
Built to clear review
Audit logging, content guardrails, and cost governance designed to align with DOE's responsible-AI direction.
We augment, never replace
Our Space Station Approach plugs flexible AI engineering into your team — amplifying the people who know the science.
Outcome-first
An intake-led method that finds the work worth doing, rules out hype, and gets to a working prototype fast.
A way of working built for
your environment.
We dock with your team
We bring flexible capacity and a deep AI skillset, then plug into the best of your internal team — not hand you something over a wall.
Clarity before code
Our intake method finds the real need, surfaces unknowns, and steers around complexity — so the build is the right build, fast.
Designed to be approved
Governance, audit, and data-control aren't bolted on at the end. It's how we architect from the first commit.
How it feels to work
with Ricochet.
Led by someone who knows the lab.
Ricochet is led by Casey Cobb — CEO, Berkeley Lab Affiliate, conference keynote speaker, and author of Flipping the Script. For close to two decades he's helped science organizations turn information chaos into well-managed, integrated systems.
That same intake-first, outcome-driven approach is now pointed at AI — with the judgment to know where it genuinely helps, and the discipline to deploy it in a way your institution can trust.
Have an AI initiative in mind?
Reach out to Casey to see how Ricochet can take it from ambition to a working, governed system — without the false starts.