Agents that act on real systems.
Plan, act through MCP tooling on the desktop, the cloud, and the OS, check their own work, and escalate when the stakes justify a human. Credentials never leave the device.
The AI our engineershave already put in production.
Agents that act on live systems, citation-grounded document intelligence, and sub-second voice. Every case study below is the architecture, the failure modes we hit, and the numbers we measured. We can walk you through any of them live.
At a glance
Each case names the constraint that made it hard: an untrusted agent on a live account, a citation with nowhere to go outside the index, audio with no upload path, a claim that cannot appear without a source.
Read the mechanism and the delivery status together. Several builds were internally tested and not deployed, or are Bigcircle's own system, and the page says so.
- Who this is for
- Buyers checking delivery experience and engineers reviewing how the systems were built.
- Topics
- AI agents
- Document intelligence
- Voice AI
- Delivery status
In short
Bigcircle states the delivery status in the same place as the mechanism. Several builds on this index were internally tested and not deployed, or are Bigcircle's own system. Each case study is the architecture, the failure modes, and the numbers measured, and any of them can be walked through live. The work clusters as agents that act on live systems, citation-grounded document intelligence, and sub-second voice.
- Executive operationsDynamic tool discoveryVenture-Backed B2B SaaS Built an AI Chief-of-Staff AgentA desktop AI chief-of-staff that plans a goal, acts across email, calendar, docs, and CRM, and checks its own work, with credentials that never leave the device. We built dynamic tool-discovery for it months before the labs made it a standard.55%80%Tasks done without a human
- SalesOn-device inferenceSeries A SalesTech Built an On-Device AI Meeting Intelligence PlatformA real-time sales co-pilot that detects a live meeting, transcribes it on-device, and writes a clean, CRM-ready summary the moment the call ends. No audio ever leaves the laptop.~2ndIn the world to ship live-meeting detection
- Cloud infrastructureHuman-gated tool executionSeed-Stage DevOps SaaS Built an AI Cloud Operations AgentA DevOps agent that turns plain-English requests into safe, validated cloud changes, using MCP tools to inspect, apply, and roll back, all scoped to your own account.10%4%Fewer failed changes
- Legal & IPCitation-bounded retrievalSeries A LegalTech Built an AI Trademark Drafting PlatformA fine-tuned LLM with RAG over a trademark and IP library, built so the model can only cite firm-approved authorities. A practicing trademark attorney tested it daily and signed off on its drafts.40%98%Five-part template adherence
- ESG & institutionalClaim-to-evidence lineageInstitutional ESG Analytics Built an AI Filing Intelligence PlatformAgentic search over dense ESG and institutional filings. It extracts the data, grounds every answer in a citation, fact-checks new documents against the knowledge base, and builds interactive reports on top.Every answerCited and fact-checked
- Fund operationsFigure-to-source lineageInstitutional Fund Manager Built an AI Reconciliation PlatformFund and portfolio management in one place. It automatically pulls in statements and brokerage data from every custodian, then handles reconciliation, dashboards, and compliance in a single view.DayshoursMonth-end reconciliation
- Market intelligenceEvidence-locked retrievalBigcircle Built an AI Prospect Intelligence EngineCompany and market intelligence at scale. Hybrid RAG over a vector database turns web-scale research into clean, structured answers, every one locked to a real source rather than invented.AfternoonminutesPer full-profile workup
- InsuranceTyped tool boundary at 900msEnterprise Insurer Built an AI Voice Claims PlatformAn insurance voice agent that handles policy, claim, and payment questions over the phone through MCP tools. Fast, fully auditable, and built to hold its response time under heavy call volume.900msTime to respond
- Real estateConstraint resolution on live inventoryPropTech Platform Built an AI Voice Property Discovery AgentOur voice agent, retargeted for real estate. Buyers explore listings by phone in English, Hindi, and Hinglish: conversational, fast, and grounded in live inventory.<1.3sTime to respond
- Sales coachingRubric-governed scoringBigcircle R&D Built an AI Sales Roleplay Coaching PlatformA voice-based sales coaching simulator. A voice agent runs realistic roleplay calls, throws objections and counter-questions, and a rubric-based engine turns each one into a skill-by-skill scorecard.20–40m2–3mManager review time
The demo is the easy part. Everything here survived the rest.
Three problems, shipped over and over.
Grounded document & data intelligence.
Citation-backed extraction and search over dense, regulated filings, with a validator that rejects anything outside the approved index. Every answer traces to a real source.
Real-time voice that holds under load.
Multilingual agents that answer on the line in about a second, verify the caller, and log every call as a structured, replayable record. Built on one runtime we reuse across verticals.
Common questions
How should I read a Bigcircle case study?
Read the mechanism and the case together. Bigcircle opens each card with the industry and the engineering that made the build hard, then the title and the measured number. Skionis reads the live AWS account before it plans, and an engineer approves a diagram of what will exist rather than the YAML. It is in production, and still demoed against a real AWS account.
What does delivery status mean on this index?
Bigcircle states how far the work got, next to the mechanism. Builds that were internally tested and not deployed, and builds that are Bigcircle's own system, sit on the same index as the AI our engineers have already put in production. Read the status with the architecture, the failure modes, and the numbers measured. Bigcircle will walk you through any of them live.
What separates the agent, document, and voice clusters?
Bigcircle separates them by the failure each build had to survive. Agents check the work before a change runs. Brandiligence's validator rejects unresolved citations, and it is in production, verified by the practising attorney it was built for. Prospex is Bigcircle's own system, in daily use on our pipeline: a claim with no retrieved source does not appear, and it is not a deployed client product. Voice reuses one runtime and logs every call as a structured record.
What can Bigcircle demo?
Any case study on this index. Bigcircle will walk you through the architecture, the failure modes, and the numbers measured, live. On AnyTeam there is no upload path for customer audio: capture and transcription stay on the rep's machine, so customer audio never leaves the laptop. It is in production inside a signed and notarized desktop app.
Let's build something that ships.
Tell us what you're building. We'll tell you whether you need an engineer embedded or the whole build led, what's achievable, and where the real bottlenecks are.