Chat is fine for experiments. Operations need a cockpit. We engineer Control Surfaces — real-time dashboards that let your team observe AI agents, approve actions, and orchestrate workflows across your tools. The interface that turns human intent into reliable execution.
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Real-time State | Zero Lag | Predictive Render
You invested in AI. You deployed agents. Now you are drowning in chat threads, losing context across tabs, and watching your team copy-paste between systems. The intelligence exists. The control layer does not.
The gap between AI capability and business value is rarely the model. It is observability, permissions, and integration. Chat tools can draft text. They cannot show you live agent state, enforce approval gates, or write safely into systems like your CRM or ERP. A Control Surface does — and it is engineered, not bolted on.
Managing AI through scattered chat windows
One command dashboard with live agent state
Context preserved. State visible. Decisions traceable.
Copy-pasting AI outputs into real systems
Direct integration — AI writes into your workflow
Less manual transfer. Fewer errors. Faster execution.
Waiting on spinners while AI “thinks”
Optimistic UI that keeps teams moving
Flow preserved. Responses reconcile when results arrive.
AI trapped in a browser tab, blind to your data
Secure context bridges to your business systems
AI grounded in your inventory, pricing, and customer history.
No proof of what the AI decided or why
Decision trails with role-based access and logs
Every action recorded. Every decision explainable. Audit-ready.
Endless evaluation and "wait-and-see" strategy
Architecture workshop and rapid prototyping
From experimental toy to production-ready control surface.
A Control Surface is not a web app with “AI features.” It is a purpose-built system with three interdependent layers — each solving problems generic dashboards ignore.
Your business truth is scattered — spreadsheets, PDFs, ticket notes, databases, and internal docs. Without structure, agents either hallucinate or require constant prompt babysitting.
We audit, clean, and model your internal data into machine-readable formats. We define schemas, build extraction pipelines, and create the retrieval layer your agents can trust. You get a single source of truth — not “best-effort context.”
AI decisions stay grounded in your actual business data. Your team stops re-explaining the same context on every run.
Classic UIs assume human-speed interactions. Agents operate differently: variable inference latency, bursts of actions, and long-running tasks. If the interface does not handle this, adoption collapses.
We engineer optimistic, real-time interfaces that keep your team in flow. Live state, queued actions, approvals, and reconciled updates — so AI can work in the background while humans stay in command.
A cockpit for AI operations: fast feedback, clear ownership, and no lost context when tasks take seconds or minutes.
Your AI tooling is isolated from your real systems. A model cannot safely read from — or write to — your CRM, ERP, billing, or internal databases without a controlled protocol layer.
We build Context Bridges using MCP (Model Context Protocol) and secure API integrations. This layer routes the right data into the model, validates outputs against schemas, and executes actions with auditability and guardrails.
Agents that do real work on real systems — with permissions, logs, and controls. Not a demo. Operational infrastructure.
Control Surfaces take different shapes depending on how your operation runs. These are the most common implementations we ship.
A unified view of agent activity, system health, task queues, and decision logs. See what is running, what is blocked, and what needs human approval — without digging through chat history.
Prospect research, follow-up drafting, and CRM updates inside one workflow. Your team works in a single place while agents enrich data and prepare next actions in the background.
A self-service portal where customers interact with agents — while you retain oversight. Monitor conversations, intervene when needed, and connect outcomes to order status, scheduling, or account data.
Ask questions in plain English and get structured answers with visual context. The key is not “no SQL” — it is governed access, traceable sources, and answers your team can trust.
Manage multi-step agent workflows with approvals, branching logic, and exception handling. When something breaks, you see exactly where — and you can intervene without restarting everything.
Audit trails, access logs, and decision rationale built into the UI. Designed for GDPR and regulated environments where “trust us” is not an acceptable control.
For the technical evaluator in the room. These are implementation details we can explain in architecture diagrams — not marketing slogans.
We show the expected state immediately while the model runs. When the final result arrives, we reconcile deterministically instead of “jumping” the UI.
Teams stay in flow even when inference takes seconds.
We design interfaces that keep working through flaky connectivity. Data writes are queued locally and synced once a connection returns.
Field teams do not get blocked by “connection lost.”
We strip PII and sensitive data before any retrieval context reaches external AI providers. Sensitive fields are masked at the pipeline layer, not at the prompt layer.
Data privacy is enforced by architecture, not by hoping a prompt behaves.
Agent outputs are validated against strict schemas before they can touch your systems. Invalid or unsafe payloads are rejected and routed for review.
No garbage-in updates in your database or CRM.
The emerging standard for AI-to-system communication. We implement MCP to make tools, permissions, and context predictable across models.
Your interfaces remain stable as providers and models evolve.
We deploy Control Surfaces close to users when it makes sense — reducing latency for global teams and improving reliability under load.
Performance becomes a property of architecture, not an endless optimization project.
These are conversations we have weekly. If any sound familiar, you are not alone — and you are in the right place.
"We have five AI tools, five browser tabs, and five different contexts. My team spends more time switching between them than actually working."
Fragmented tooling destroys productivity. Context gets lost between systems. Nobody has a reliable view of what is happening right now.
A unified Control Surface that consolidates AI work into one dashboard with persistent state and clear ownership.
"The AI thinks for 10 seconds, and by the time it responds, my team has already context-switched to something else. Adoption is terrible."
LLM latency breaks user flow. If people have to wait without feedback, they stop trusting the tool and revert to manual work.
Optimistic UI architecture with real-time state: immediate feedback now, deterministic reconciliation when results arrive.
"Our compliance team will not approve AI tools because there is no audit trail. We cannot prove what data the AI accessed or why it made decisions."
Regulated environments demand visibility and control. Chat-based interfaces rarely provide decision documentation or access logs.
Built-in audit trails, PII sanitization, access controls, and decision logging — designed in from day one.
"The AI is powerful but blind. It cannot see our inventory, our pricing, our customer history. So we copy-paste constantly to give it context."
Without integration, every run requires manual context injection. Automation becomes a copy-paste ritual.
Intelligence Bridges that connect agents to your internal systems so context is retrieved and validated automatically.
"I do not know what the AI is doing. It is a black box. When something goes wrong, I have no way to understand why or prevent it next time."
Lack of observability turns AI into operational risk. Errors compound without detection, and trust erodes with each unexplainable outcome.
Control Surfaces expose state, inputs, actions, and outcomes — making agent operations observable and manageable.
Models Drift. APIs Change. We Watch the Watchmen.
"Can't you just build this once and hand it over? Why ongoing investment?"
Because AI infrastructure is not static. Models change behavior. Providers update APIs. Your data and workflows evolve. A Control Surface is a living system that needs calibration, monitoring, and disciplined upgrades. We do not sell “maintenance.” We keep your agent operations reliable.
We evaluate model options and route workloads to the best fit for cost, latency, and quality — without rewriting your product every time the frontier shifts.
We track outputs against your source-of-truth data and alert on drift. When an agent starts making confident mistakes, we catch it early.
Circuit breakers and guardrails for unsafe behavior. If an agent attempts unauthorized access or produces risky actions, it is stopped and escalated for review.
As models add new capabilities (better reasoning, faster inference, new modalities), we test what matters for your workflows and roll upgrades safely.
Your Control Surface can work across providers. We keep the interface stable and abstract the intelligence layer so you can switch models without rebuilding the product.
For European clients: we deploy on EU-resident infrastructure when required and design for GDPR-aligned data handling. Frankfurt and Zurich availability zones are common deployment targets.
Decision trails, reasoning logs, and data access records are first-class features. When someone asks "why did the agent do this?" you can answer with evidence.
When AI services fail (and they do), the interface continues with reduced capability instead of hard-crashing. Human workflows keep moving.
Full source code delivery. No proprietary black boxes. If we part ways, you keep the system and can evolve it with your internal team.
Answers to common questions about this service.
Every hour your team spends copy-pasting between AI tools and business systems is lost leverage. Every decision made in a chat thread is a decision without durable context. Control Surfaces turn AI from “helpful” into operational.
Book an Architecture Workshop. We map your current AI touchpoints, identify failure modes (latency, permissions, integration, auditability), and design a Control Surface that your team can run every day — not just demo.
No commitment required • Free consultation • Response within 24h