We Build Intelligent Systems That Run Your Business.
AI Agents, Intelligent Automation, and Seamless Business Integrations.
- Core service disciplines
- 06
- Core service disciplines
- Automated operations
- 24/7
- Automated operations
- First integration design
- API
- First integration design
An engineering team for the intelligent enterprise.
PREDICT AI designs, builds, and operates AI systems for US businesses. We combine AI agents, process automation, and robust software integrations into one coordinated operating layer — so work moves between your tools without anyone copying and pasting.
Mission brief
Most companies don't need another app. They need the apps they have to work together — and to handle the repetitive decisions that slow their people down. That's the system we build.
Strategy
Process mapping
Engineering
Agents & integrations
Operations
Monitoring & tuning
- P-01
Built around your stack
We connect the platforms you already pay for instead of forcing a rip-and-replace. Your CRM, ERP, inbox, and data stay where they are.
- P-02
Humans stay in control
Every agent has defined permissions, approval gates for sensitive actions, and a complete audit trail your team can review.
- P-03
Measured by outcomes
We define success metrics before we write code — hours saved, cycle time, error rates — and instrument systems to track them.
Six disciplines. One operating system for your business.
Select a capability to inspect it. Each one can stand alone — or plug into the others as your automation program grows.
SVC-01 · Capability profile
AI Agents & Autonomous Workflows
We design goal-driven AI agents that read context, call tools, and complete multi-step work — with guardrails, approvals, and full audit trails so your team stays in control.
Capabilities
- Tool-using agents with role-based permissions
- Human-in-the-loop approvals for sensitive actions
- Multi-agent orchestration for complex workflows
- Observability: traces, costs, and outcome logging
Example use cases
- Qualify inbound leads and draft follow-ups in your CRM
- Triage support tickets and resolve routine requests
- Monitor inventory and open purchase orders for review
From manual process to autonomous system in five phases.
A proven delivery loop that de-risks AI projects: start with a measurable pilot, then scale what works.
- 01
Discover
We interview your team, map current workflows, and identify where automation creates measurable value.
Output → Opportunity map + priorities
- 02
Architect
We design the system: data flows, integrations, agent roles, security boundaries, and success metrics.
Output → Technical blueprint
- 03
Build
We ship in short iterations, connecting real systems in a staging environment and testing against real scenarios.
Output → Working pilot
- 04
Deploy
We roll out with monitoring, permissions, and runbooks — plus training so your team knows how everything works.
Output → Production launch
- 05
Optimize
We track performance, tune models and rules, and expand automation to the next highest-value process.
Output → Continuous improvement
Run a workflow. Change the inputs. Watch the path change.
A working simulation of three common automations. Edit the sample inputs — the rules engine recalculates scoring, approvals, and routing in real time.
Workflow pipeline
Preview
Execution log
> Ready. Press Run workflow to execute with the sample input._
Step inspector
The pipeline above is a live preview of the path this input will take.
Click any step to see what it does, or run the workflow to watch data move between systems — the 3D core above reacts while it runs.
Every system connected. Every handoff automated.
We build the integration fabric that lets data and decisions flow between the platforms US businesses rely on. Hover a system to trace its data flows — the 3D network reacts too.
Integration fabric · topology
8 example systems
Selected system
CRMSalesforce
Typical automated data flows:
- 01Leads & opportunities
- 02Account updates
- 03Activity logging
Integration patterns
- Webhooks
- Real-time events the moment something changes
- REST & GraphQL
- Reliable reads and writes with retries
- Event streams
- Queues that absorb spikes and never drop data
- Scheduled sync
- Batch reconciliation for systems without events
- Files & SFTP
- CSV, EDI, and PDF exchange with legacy partners
- Databases
- Direct, read-only connectors to operational data
Platform names are shown as examples of systems we can integrate with. All trademarks belong to their respective owners; no partnership or endorsement is implied.
A layered architecture engineered for reliability.
Every PREDICT AI system is built on the same five-layer ecosystem. Select a layer to explore it — the corresponding ring of the command core lights up.
Layer L4
Agent Orchestration
Planning, tool calling, memory, and multi-agent coordination — with policies that define what each agent may do.
- Task planning
- Tool registry
- Short & long-term memory
- Approval gates
- 01
Security by design
Least-privilege access, encryption, secrets management, and audit logs on every integration.
- 02
Vendor-neutral models
We choose models by evaluation results and cost — and keep you free to switch.
- 03
Observability
Traces, costs, and outcomes for every agent action and workflow run.
- 04
Documented handoff
Runbooks, architecture docs, and training so your team owns what we build.
Let's build the system that runs your business.
Tell us about the process you want to automate or the systems you need connected. We'll come back with practical next steps.
Reach us directly
What happens next
- 01
Inquiry review
A solutions engineer reads your message and maps it to the right expertise.
- 02
Discovery call
A focused conversation about your processes, systems, and goals.
- 03
Proposal
A scoped plan with architecture, timeline, and a clear pilot milestone.
Project inquiry · secure channel
Ready