01
Five teams, five invoice agents
Each business unit reinvents extraction logic, approval routing, and HITL handling from scratch, with no shared library and no awareness the other four exist.
Agentic AI Launchpad
Every business unit is quietly building its own AI agent. That's the problem.
Five business units, five invoice agents, five different models, five different security reviews, zero reuse. And every one of them stuck in the same queue, waiting on the same handful of overstretched AI engineers. That's not innovation. It's shadow AI with better branding, bottlenecked by a team that can't scale.
30+
Agents
87
Modules
3–4 d
Build time
99.1%
Uptime
The Cost of Fragmented AI
Without a platform, every AI initiative is a one-off project pretending to be a strategy.
This is the pattern across almost every enterprise moving fast on AI: pilots multiply, none of them talk to each other, and nobody can tell you with confidence what's running in production right now.
Why a Platform. Not Pilots.
Six reasons enterprise AI needs to be institutionalised. Not improvised.
These aren't features. They're the structural reasons a platform approach beats a thousand disconnected prototypes, for the business, for engineering, and for whoever has to answer for it in an audit.
Ready to see your first agent live in 3–4 days?
Bring your use case. We return an architecture, a coverage check, and a cost estimate. Same session.
Proprietary Framework · Affine
The Agentic
Launchpad
From AI ambition to live production agent in weeks. Not quarters.
The Agentic AI Launchpad is a reusable enterprise AI platform that accelerates the design, deployment, governance, and scaling of operational-grade AI agents. It does not ask your team to start from a blank canvas.
It gives them a working foundation: 30+ battle-tested agent components, a live visual build environment, and governance wired in at every layer.
Book a Discovery Session30+
Certified reusable
agents in the catalog
87
Production-tested
agent modules
3–4 d
Typical build time
for a new use case
99.1%
Uptime across
the live agent fleet
How It Works
Seven capabilities that collapse the build timeline
From the first plain-English description of a problem to a governed, production-grade agent. All without leaving the platform.
InputA plain-English problem description
01
Intake
Interactive Wizard
Users describe their business problem in plain English through a guided interface. No technical specification required to get started.
02
Blueprint
Live Visual Blueprinting
The platform converts the input instantly into an interactive, non-linear business flow diagram. Business users can see the entire logic, validate it, and modify it. All before a single line of code is committed.
03
Catalog
Smart Catalog Mapping
As the blueprint takes shape, visual nodes highlight which agents are catalog-ready and reusable, and which need to be built from scratch. Teams know exactly what they are inheriting before the project starts.
04
Power
Multi-Model & Multi-DB Power
Supports multiple large language models running simultaneously for complex problem types. Database connectivity runs through MCP, linking to multiple sources in parallel.
05
Build
Git-Powered App Creation
Integrates directly with your Git repositories. Pulls existing agent codebases, combines them, and deploys a new application automatically, from code to running system, without manual assembly.
06
Connect
Unified Connectivity
Custom and pre-built agents connect through ACP, giving developers a consistent, friction-free build experience regardless of how many agents are involved in a given workflow.
07
Govern · Runs throughout
Automated Governance
An Eval Agent runs continuously, in real time and in batch, validating correctness, responsibility, and guardrail compliance at every step. Governance is not a final checkpoint. It runs throughout.
Platform in Action
What Institutionalised AI Looks Like on the Platform
Eight screens from a live deployment. Every principle above is something you can click on: named agents, real accuracy metrics, governance wired in at every step.
Named, production-proven agents. Not generic templates.
Click any module for accuracy, latency, and cost per run
Approved model and library stack enforced by default
HITL thresholds and routing rules configured inline
Workspace Dashboard
Every active agent, workflow, and session metric in one view. Your team always knows what's running, what's queued, and what needs attention. No chasing status across five tools.
The Architecture
A layered, modular stack that slots into your existing enterprise environment
Each layer is independently composable. Add an orchestration layer without rebuilding the knowledge layer. Swap a connector without touching agent logic.
Production AI AgentsEnterprise DeploymentsGoverned at Scale
Semantic ExplorerVector RetrievalData Access Abstraction
Task PlanningAgent RoutingState ManagementMemory ManagementError Recovery
Semantic AgentFormatter AgentGeneration AgentValidation AgentRetrieval Agent
Context Window ManagementDocument IngestionSLM SupportMulti-LLM Routing
SalesforceMajor ERP SystemsCloud PlatformsData WarehousesEnterprise Connectors
Access Control & IAMMonitoring & ObservabilityEncryption & Data PrivacyHigh Availability & DRScalable Cloud Infrastructure
End Solution at top · Foundation at base · Each layer independently composable
Built on
Multi-LLM ArchitectureMCP ConnectorsGit-native DeploymentACP OrchestrationEval Agent (real-time + batch)87 Certified Modules
How We Work
From idea to production AI in weeks
The first agent costs the most. Every subsequent agent becomes faster to deploy, more cost-efficient, and easier to scale. The architecture is already there.
Discover
“Define the target before building the weapon.”
In this phase
- AI readiness assessment and data landscape audit
- Use case identification and prioritisation
- ROI modelling and business case quantification
- Agent architecture and feasibility blueprinting
Deliverable
Signed-off agent architecture and ROI business case
Each phase compounds. The first agent costs the most; the architecture carries the rest.
Why the Launchpad
What changes when you stop building from scratch
Not a better way to build agents. A fundamentally different starting point.
Traditional AI Delivery
Agentic AI Launchpad
Every team starts from a blank repository, regardless of how many similar agents already exist elsewhere in the org
Every build starts with a coverage check against 87 certified modules already proven in production
Model and library choice is left to individual engineers, with no enforced standard and no visibility for security
Approved models and libraries are enforced at the architecture level, not a policy anyone needs to remember
Knowledge of what worked leaves with the person who built it. No versioning, no benchmark record.
Every successful build becomes a versioned, benchmarked module the next team can reuse directly
Business users wait weeks for a spec to be translated into something engineering can build
The process owner describes the problem conversationally and gets an architecture back the same session
Governance is retrofitted after the fact, usually after an incident or an audit finding
Drift detection, audit logs, and HITL controls are inherited automatically by every new agent
Cost and ROI are estimated after the build, not before it starts
Coverage, cost, and accuracy are visible before a single line of architecture is committed
Industry Templates
The Launchpad in production, across industries
Purpose-built agent templates for your sector, deployed in weeks, not quarters.
CPG & Retail
- Retail execution agent deployed in 5 weeks
- PDP generation at catalogue scale
- Demand sensing agent live across 40+ SKUs
- Dynamic pricing optimisation running continuously
Manufacturing
- Predictive maintenance reducing downtime by 35%
- Quality assurance agent catching 98% of defects
- Production planning optimised in real time
- Supplier risk intelligence running around the clock
High-Tech & Software
- Agentic code review cutting review time by 60%
- Multimodal querying engine deployed to production
- Market intelligence agent surfacing signals daily
- Customer 360 agent serving 2M+ profiles
Financial Services
- Claims validation agent processing 10x volume
- Risk assessment agent reducing false positives by 40%
- Compliance monitoring fully automated
- Document processing agent meeting SLA 100% of the time
Case Studies
Proof, Not Promises.
Every result below came from a platform build. The modules that delivered it are in the catalog, ready for the next team.
“The first agent costs the most. Every one after should cost less, because the knowledge of how to build it has already been certified and stored, not locked in one engineer's head.”
Invoice extraction, live in production
A finance team’s manual extraction workload, handed to a governed agent.
Measured Impact
- →94.2% extraction accuracy in production
- →12-minute manual processing cut to 90 seconds
- →Built in days from existing certified modules
- →Human review only on flagged exceptions
Shelf compliance at audit scale
Merchandising audits that used to take days now run in minutes.
Measured Impact
- →88.7% shelf-compliance accuracy
- →12,000+ SKU placements checked per audit cycle
- →Exceptions surface in minutes, not days
- →The same module reused across store formats
Standards drafting, evaluation-hardened
First-draft quality lifted cycle over cycle, then captured for reuse.
Measured Impact
- →91.5% standards-drafting accuracy
- →Up from 60% first-draft quality
- →Hardened over three annotation-driven evaluation cycles
- →Institutional knowledge captured and reused