Turn your proprietary research into a trusted, cited answer engine.
Analysts and strategy teams ask questions in plain language and get answers grounded exclusively in your own newsletters and market data — never the open internet, never a guess. Every material claim ships with a citation back to the source. Production in 13 weeks, five-person senior team.
4.9“It’s been a really positive experience working with Sphere. The resources are skilled, the communication is always responsive, and the deliverables are consistently high quality.”
Ben Crawford, Senior Product Manager, Enova Financial
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See a grounded, cited answer built from a sample of your own content.
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Every AI Knowledge Base Demos Well. Few Can Show You an Honest “I Don’t Know.”
A slick chatbot demo tells you nothing about what happens when someone asks a question outside its evidence. Here’s what actually separates a Market Intelligence Copilot analysts trust daily from one that stalls after the first confidently wrong answer.
The Pattern Behind Stalled AI Pilots
A generic chatbot tuned to always sound helpful — which means it will produce a fluent, confident answer even when it has no real evidence behind it.
A working demo on five friendly questions, then no real answer for what happens when an analyst asks something the archive does not actually cover.
A vendor that cannot show you where a specific number or quote in an answer came from — citations that gesture at "our data" instead of a specific source.
How Sphere Builds the Copilot
Every architectural decision reinforces one rule: no claim reaches the user without support from your own material — never internet search, never unsupported model knowledge.
Numbers use structured data, interpretation uses your newsletters, forecasts stay client-sourced, and no evidence means an honest non-answer — enforced in the pipeline, not left to a prompt.
21+ years of enterprise delivery experience, applied to a fixed-scope, 13-week build — not an open-ended AI experiment.
How Does a Question Become a Cited Answer?
Four steps, the same path every time — whether the question needs a quote from a newsletter, a number from structured data, or both.
Ask
A user asks a market question in plain language inside a lightweight chat interface.
Select
The system decides whether the question needs newsletter evidence, structured data, or both.
Retrieve
It pulls relevant newsletter passages and/or runs calculations against the structured datasets.
Answer
A rendered answer is returned with inline citations back to the source material.
If a question has no supporting evidence in your material, step four returns an honest insufficient-evidence response instead of a plausible guess.
See This Running Against a Sample of Your Own Content
Bring a handful of newsletters or a sample dataset to a 30-minute demo — leave with a feasibility read and a look at what a cited answer from your own material actually looks like.
Book a DemoHow Do You Prevent the AI From Making Things Up?
The system’s value depends on being trustworthy. Every architectural decision reinforces one rule: no claim reaches the user without support from your own material.
Numbers use structured data
Numerical claims draw from structured datasets when authoritative data exists.
Interpretation uses newsletters
Interpretive and narrative claims rely on relevant newsletter evidence.
Forecasts stay client-sourced
Forward-looking answers use only client-provided forecasts or expectations.
No evidence, no answer
Unsupported questions return a clear, honest insufficient-evidence response.
The rule is enforced in the retrieval and generation pipeline itself, not left to a prompt instruction an analyst could accidentally override. If a claim has no citation, it does not ship as an answer.
Organizations Around the World Trust Us
For more than 21 years, Sphere has helped organizations build, modernize, and scale technology platforms across AI, data, cloud, and software engineering.
Hear From Teams Sphere Has Delivered For
The Kinds of Questions It’s Built to Answer
The pattern is always the same: one answer grounded in narrative evidence, one grounded in a number — each carrying the citation that backs it.
From your newsletters
- “What has our research said about [industry trend] over the last two quarters?”
- “How does our view on [market] compare across the regions we cover?”
- “What have we published on [named competitor or category]?”
From your structured data
- “What is the forecast growth for [segment] over the next five years?”
- “Which category is forecast to grow fastest through 2030?”
- “How has share changed by segment or geography?”
A System Analysts Use Daily, Not a One-Time Demo
Every Market Intelligence Copilot engagement is scoped around the same question: can every claim it makes be traced back to something you actually own?
Citation Coverage as a Design Target
Every material claim ships with a traceable citation, verified against an agreed correctness threshold before launch.
A Knowledge Base That Keeps Growing
Newsletters and structured data can be added on an ongoing basis without manual database intervention or downtime.
MCP-Compatible From Day One
Plug the same grounded intelligence into your own tools, websites, and AI assistants without building a second answer path.
Client Ownership
Your newsletters and structured data remain your own proprietary assets — you own the resulting architecture, code, and operating knowledge.
How Long Does It Take, and What Does It Cost?
A comparable Market Intelligence Copilot — architecture through production deployment and handover — has been delivered as a single, fixed-scope engagement.
Discovery & Architecture
Weeks 1–3. Functional scope, architecture, and semantic model agreed before a line of ingestion code is written.
Data Ingestion
Weeks 2–6. The newsletter and structured-data foundation, including schema design and cleanup.
Grounded Answering
Weeks 4–8. Conversational intelligence and the citation logic that ties every claim back to a source.
Validation & Handover
Weeks 10–13. End-to-end validation, UAT, production deployment, and knowledge transfer.
One solution, one investment — solution architecture, AI engineering, front-end and back-end development, and project management through deployment and handover.
Based on a comparable Market Intelligence Copilot already delivered as a single fixed-scope engagement with a five-person senior team. Your scope is confirmed in discovery before anything is committed.
What a Grounded Copilot Changes
Three illustrative engagements modelled on how research and data businesses put a grounded, cited copilot to work — the figures are projected scenarios, not measured client results.
4.9/5 on Clutch. 21+ years of enterprise engineering.
TOP AI CODE GENERATION COMPANY UNITED STATES 2025
TOP AI TEXT GENERATION COMPANY FLORIDA 2025
TOP APP DEVELOPMENT COMPANY MANUFACTURING 2025
TOP ARTIFICIAL INTELLIGENCE COMPANY UNITED STATES 2025
TOP CHATBOT COMPANY UNITED STATES 2025
TOP RECOMMENDATION SYSTEMS COMPANY UNITED STATES 2025
GLOBAL RECOGNITION AWARDS 2026
BEST IN AI FOR DOCUMENTATION VALIDATION 2026
BEST IN AI POWERED INVOICE AUDITING 2026
GLOBAL TECH WINNER 2026
GLOBAL GENERATIVE AI AWARD 2026 WINNER
Sitting on Proprietary Research You Haven’t Made Queryable?
Whether it’s years of newsletters, a structured spend dataset, or both — Sphere scopes a fixed-timeline path to a grounded, cited copilot analysts actually use.
Book a DemoIs a Market Intelligence Copilot Right for Your Organization?
This is built for any organization sitting on proprietary content and data it has not yet made queryable — research firms, media and ad-intelligence shops, analyst houses, consultancies, industry associations, B2B publishers, and subscription research providers.
- Analysts spend real time digging through past newsletters and spreadsheets to answer a client question.
- You publish proprietary research, newsletters, or structured market data that already exists but is not searchable.
- A generic AI chatbot is too risky — you need every answer traceable to a real source, not a plausible guess.
- You want to turn existing IP into a new product surface for clients, not create more content to write.
- You need a fixed-scope, fixed-timeline delivery rather than an open-ended AI experiment.
Built for Organizations Whose Product Is What They Know
The grounding rules and the citation guarantee stay the same across every segment — only the source material changes.
More on Grounded, Cited AI Over Your Own Content
Market Intelligence Copilot, Answered Directly
Ready to See a Cited Answer Built From Your Own Content?
Book a demo and bring a sample of your newsletters or structured data. Fixed-scope delivery, 13 weeks to production, senior team only.
No RFP required · fixed-scope or dedicated pod · discovery call within days.
4.9