Revenue Orchestration AI for Dynamics 365 for Sales.
Less than 1% of cold outreach gets a reply. We answer the only question that earns the meeting: what does this buyer need to learn that they don't yet know?
Account intelligence the buyer hasn't seen yet.
Fourteen-plus outside-in sources, fused per account. Filings, hiring data, vendor case studies, technographics, patents, M&A, earnings — every claim pinned to a primary source.
The best of every frontier model — picked per task, not locked in.
Your motions, ICP, and GTM profile — the way your team actually sells.
14+ outside-in sources, classified by entity type, cited per claim.
Multi-model ReAct agent. Claude · GPT · Gemini — orchestrated, not locked in.
One account. Three opportunities. Forty-one seconds.
A live brief on Florida Crystals Corporation — generated end-to-end by the orchestration engine, with 47 citations across 14 sources.
We leverage every researcher. Then add the precision they miss.
An eight-type entity classifier rejects counterparty documents before they pollute the brief — so when Akerman LLP shows up in a Florida Crystals 10-K because they're outside counsel, we drop the doc honestly instead of guessing.
The data points are always moving.
Our synthesis is what connects them.
Any AI tool can do deep research on a frozen moment in time. The moat is the synthesis layer that re-connects the dots every time the dots move. Earnings post, executives change, a patent files, a job posting appears, a vendor case study gets pulled, a CFO speaks at a conference — OrkastraD365 doesn't just re-summarise; it re-weighs the evidence, kills hypotheses that no longer hold, promotes ones that just got stronger, and runs the whole thing through your GTM and sales motions so what reaches the buyer reads like an unsolicited proposal, not a summary.
It's the difference between a snapshot and a living point of view. Last week, strong evidence the CFO was hiring transformation leaders. This week, autonomously, the CEO speaks at an industry event on the same theme and the CIO shows up at an SAP conference on a related topic — the graph reshapes, the priority climbs, the next-best-action changes. Fifteen frontier models, fanned out across thousands of touchpoints, re-running the synthesis until the moment the buyer is most likely to engage. A Big-3 senior partner working your book, twenty-four hours a day.
Four surfaces. One brief. Your seller becomes the buyer's most valuable asset.
Account briefs, plans, and the next-best-action — all in one workspace.
Briefings and signal alerts where your sellers already live.
8-step pipeline runs research, strategy, assets, and outreach.
Declarative agent — answers from the same brief, in the seller's flow.
See it on one of your accounts.
Tell us the account. We'll generate a live brief — sources, citations, and all — before our first call.
Questions buyers actually ask.
How is this different from sales-intelligence tools we already use?+
Most intelligence tools stop at the firmographic. OrkastraD365 starts at the entity type — law firm, accounting firm, healthcare system, public US company — and applies a per-type evidence hierarchy. The brief you read is grounded in source documents (10-Ks, hiring data, patents, technographics, court records) that match the company you're actually selling to.
Do we need to rip out Dynamics 365?+
No. OrkastraD365 layers on top of D365 for Sales. Accounts, contacts, and seller coverage sync from Dataverse; we add the intelligence, the plan, and the next-best-action surfaces. Your CRM stays the system of record.
Where does the AI run? Who sees our data?+
OrkastraD365 is published on Azure inside your Microsoft estate, with model calls fanned out to the frontier providers — Anthropic Claude, OpenAI, and Google Gemini — through governed enterprise endpoints. Tenant data is isolated by tenant ID on every query path. Published briefings are scoped to per-link access tokens, not public URLs, and rotate per recipient.
Can sellers use this inside Microsoft Copilot for Sales?+
Yes — we ship a declarative agent (Copilot Cowork plugin) that answers account-scoped questions from the same brief the web app shows. Read-only in v1; write actions are deferred until the auth bridge has soaked in production.
How is this different from Copilot Cowork + WorkIQ, Claude, or ChatGPT doing the research?+
Deep research is table stakes — any frontier model can summarise a company. The moat is what happens after the research: synthesis, interpretation, and prescription. OrkastraD365 acts like a Big-3 consultant (Bain, McKinsey, BCG) — it finds the non-obvious insight that teaches the buyer something they don't already know, and then applies your company's GTM strategy and sales motions on top of it so what arrives in the buyer's inbox reads like an unsolicited proposal: here is the problem we believe you have, here is how we would solve it if we owned the outcome, here is the next conversation. And it never stops. Last week, the LLMs gave us strong evidence the CFO was hiring transformation leaders. This week, autonomously, all fifteen models found that the CEO attended an industry event on the same theme and the CIO was at an SAP conference on a related topic — meaning SAP is probably already in the conversation and the window is closing. That's thousands of touchpoints, fused, weighted by your tenant's own won/lost outcomes, and dropped on the seller's desk with the next-best-action ready to fire. A single chat agent gives you one good answer to one question. OrkastraD365 gives you a continuously sharpening point of view across your entire book.
What does 'Earn the meeting' mean?+
Sellers shouldn't ask for time they haven't earned. Every briefing we publish is built around what the buyer would find useful — a synthesis of their business context, signals, and the recommended next conversation — not a pitch. The form below is the same idea: tell us what you'd like to fix, and we'll come back with something specific.