Rainbird is now available on Google Cloud Marketplace. Regulated enterprises can now buy Rainbird's decision automation platform through their existing Google Cloud account, with eligible purchases counting toward committed spend. Bringing new software into a regulated enterprise usually means vendor onboarding, security questionnaires, legal review and new supplier approval. That can take months, and it often takes longer than the technical evaluation itself. Buying through Google Cloud Marketplace uses commercial rails most Google Cloud customers already have in place. Billing flows through your existing Google Cloud account, so there's no new supplier to set up and no separate contract cycle to run. The listing covers the full Rainbird platform, which turns regulations and policies into deterministic decisions. Every decision comes with an evidence tree showing how the conclusion was reached and which knowledge it rests on. Read the announcement: rainbird.ai/rainbird-is-now-… #RainbirdAI #GoogleCloudMarketplace #DecisionAutomation #FinancialServices

Our CTO Ben Taylor has been testing one of the newest AI models on a hard question: can AI be fast and still explain its decisions? @typesafeai new Jev model reads messy human language and matches it to a fixed set of answers in a fraction of a second. What it can't do is apply your policy or explain its choice. So Ben paired it with the Rainbird Reasoning Engine. Jev reads what people write. Rainbird applies the policy, makes the decision and shows exactly how it got there. Between the two sits what Ben calls a trust boundary. He tried to smuggle bad instructions across it to see what would happen, and he's candid about what still needs testing. Read the full write-up, including the code to try it yourself: bentaylor.co.uk/posts/jev-an… #NeurosymbolicAI #DecisionAutomation #RainbirdAI

We're pleased to share that Rainbird has again emerged as a Major Player in IDC MarketScape: Worldwide Decision Intelligence Platforms 2026 Vendor Assessment. Rainbird was built on one idea: when a system makes a decision that matters, it should be able to show how it got there. That's still what we build, and it's good to see it recognised in an independent assessment of the market. There's more on what the assessment is, what we do and why it matters now in the full post: rainbird.ai/rainbird-named-a… #RainbirdAI #DecisionIntelligence #DecisionAutomation #IDCMarketScape

Turn written policy into a decision agent in hours. Deterministic. Auditable. Yours! In regulated work, a decision you can't evidence is a decision you can't defend. That's why automating regulated processes with LLM agents is so difficult. Today we took a step towards changing that by introducing RAKE: Rainbird's Agentic Knowledge Engineering workbench. Point RAKE at the documents your decisions run on and it researches, drafts and live-tests a graph your experts can review and sign off. What you get is a deployed decision agent with an evidence tree behind every answer, no LLM in the reasoning path, and no token cost at runtime. From written policy to a deterministic, auditable decision agent in hours. When a working graph takes hours rather than weeks, the long tail of regulated decisions, the ones that never justified a full build project, comes into reach. That's the ambition behind RAKE: making institutional expertise computable at scale. We're onboarding a small number of teams at a time. If you want to be one of them, register for early access and tell us the decision you want to automate. Visit rainbird.ai/rake

Your agents are clever. But not one of them has read your policy. Agentic AI is genuinely good at most of what happens around a regulated process: reading documents, gathering evidence, drafting the summary, moving the case along. Then the process narrows to one step. Approve or refer. Pay or investigate. Compliant or not. That step still sits with a handful of experts, because LLM-agents can't own it. They give different answers to the same question. They can't guarantee the policy was applied. And when the regulator asks why, "the model predicted it" isn't an acceptable answer. Rainbird takes a different route. We encode how your experts actually reason, as a knowledge graph, and apply it to every decision. Same case, same answer, every time. Each decision comes with an evidence tree showing the rules, the evidence and the reasoning behind it, in language a person can read. Agents orchestrate. Rainbird decides. The evidence tree shows why. We've just rebuilt the Rainbird website around this argument. Have a look: rainbird.ai/platform #AgenticAI #DecisionAutomation #NeurosymbolicAI #ExplainableAI #RegulatedIndustries #RainbirdAI

Working with Generative or Agentic AI? Then you already know documents ≠ decisions. See how Rainbird turns existing docs into structured knowledge your systems can actually reason over. Live demo + Q&A. linkedin.com/events/74150110…

Co-Founder and CEO @jamesduez delivers the latest on how businesses are using Knowledge Graphs to unleash the true potential of 'human-first' automated decision-making. #intelligentautomation #forbes

Working alongside a team of specialist tax advisors, Rainbird has developed a tax judgement and decision-making tool that automates complex, human-like judgements in the same way an expert tax specialist would. zcu.io/o8yP

Rainbird is fundamentally different to RPA and rules engines. And that's good news if you're trying to scale intelligent automation. Get our concise guide to what Rainbird is, how it works and why you need it: zcu.io/uBFn #intelligentautomation #AI #automation

Rainbird is fundamentally different to RPA and rules engines. And that's good news if you're trying to scale intelligent automation. Get our concise guide to what Rainbird is, how it works and why you need it: zcu.io/uBFn #intelligentautomation #AI #automation

Rainbird is fundamentally different to RPA and rules engines. And that's good news if you're trying to scale intelligent automation. Get our concise guide to what Rainbird is, how it works and why you need it: zcu.io/uBFn #intelligentautomation #AI #automation

Rainbird is fundamentally different to RPA and rules engines. And that's good news if you're trying to scale intelligent automation. Get our concise guide to what Rainbird is, how it works and why you need it: zcu.io/uBFn #intelligentautomation #AI #automation

Rainbird is fundamentally different to RPA and rules engines. And that's good news if you're trying to scale intelligent automation. Get our concise guide to what Rainbird is, how it works and why you need it: zcu.io/uBFn #intelligentautomation #AI #automation

When organisations in regulated industries deploy AI without proper infrastructure, they are taking on (avoidable) risk. Learn what a human-down, data-up infrastructure is, and why it’s changing how organisations approach #AI and #automation. zcu.io/HqIB

Rainbird is fundamentally different to RPA and rules engines. And that's good news if you're trying to scale intelligent automation. Get our concise guide to what Rainbird is, how it works and why you need it: zcu.io/uBFn #intelligentautomation #AI #automation

43% of organisations have accelerated their rollout of AI since the start of the COVID-19 pandemic, according to @IBM. Learn the three principles every AI-driven organisation must adopt. zcu.io/5OWM #intelligentautomation #AI

When organisations in regulated industries deploy AI without proper infrastructure, they are taking on (avoidable) risk. Learn what a human-down, data-up infrastructure is, and why it’s changing how organisations approach #AI and #automation. zcu.io/HqIB

Rainbird is fundamentally different to RPA and rules engines. And that's good news if you're trying to scale intelligent automation. Get our concise guide to what Rainbird is, how it works and why you need it: zcu.io/uBFn #intelligentautomation #AI #automation