Covasant | Context, Orchestration & Reasoning for your Agents
Introducing Agentic Enterprise Intelligence Platform SERAA
Your AI pilots aren't the problem. AI Production is.
Most enterprises today have dozens of AI initiatives and almost no AI in their operating models. SERAA is the intelligent layer that turns fragmented investment into intelligence that understands your business, reasons about your business goals, acts inside your systems under real governance, and gets better every time it runs, in our cloud, in your VPC, or fully air-gapped on your own hardware.
100+ Data source connectors, mastered into governed records
1 of 7 AI-natives worldwide on Google Cloud's Gemini Enterprise Transformation program.
Cloud · VPC · Air-gapped Runs where your enterprise already runs, down to no Internet at all
SBAC Scope-based access control across systems, org, and projects
Don't bolt AI onto yesterday's workflow. Reimagine the workflow with AI.
Traditional automation follows steps somebody wrote in advance. Agentic systems pursue a business outcome and work out the steps themselves, which is a different thing to buy, and a different thing to govern.
The software era
Human → UI → Application → Workflow → Transaction
CLICK · SEARCH · ENTER · APPROVE · EXECUTE · REPEAT
The intelligence era
Human → Intent → Intelligence → Execution → Outcome
GOAL · UNDERSTAND · REASON · ACT · GOVERN · LEARN
You can build an AI demo. Can the demo run your business?
Real enterprises have complex workflows. Data sits in forty systems. Workflows cross six departments. Decisions carry consequences and regulators. An AI model that dazzles in a sandbox meets none of that.
Your estate todayWith SERAA
sales copilot
document Q&A
analytics bot
support assistant
workflow agent
forecast model
ops assistant
Governed by design
SERAA
Operating layer
Understands
Reasons
Acts
Learns
Secure · Compliant · Auditable
Deploy where it makes sense for you
CloudYour VPCAir-gapped
Conflicting context
Different definitions, owners, and data.
Manual handoffs
Humans stitch work across tools and teams.
Governance gaps
Policies, access, and audit vary by team.
Little measurable impact
Hard to track value or prove outcomes.
Unified business context
One model of your data, processes, and goals.
Governed action in real systems
Act inside the tools and workflows that run your business.
Measurable business outcomes
Impact you can see. Value you can prove.
Siloed teamsDuplicated workInconsistent dataNo orchestration
Many initiatives Dozens of tools and pilots running in parallel.
Multiple owners Owned by different teams with different priorities.
No shared context Data, definitions, and metrics are not aligned.
Hard to govern Inconsistent controls, access, and audit across teams.
100+ data connectors Connect anything. Ingest, unify, activate.
Enterprise governance Trust at every step. Built for audit and scale.
Sense. Evaluate. Remember. Act. Assure.
Five things intelligent action needs, in the order it needs them. Four products, and one governance layer across all of them. Each layer stands alone and pays for itself. Most enterprises start with one, and every one of them runs inside a perimeter that you choose.
Sense
Notice what your systems never wrote down. Meetings, market feeds, and field signals, captured, confidence-scored, and linked back to source.
Evaluate
Reason across everything you already own. SQL, vector, and graph retrieval composed into one chain, with the audit trail attached to the answer.
Remember
Keep what worked, once a person approves it. A layer hierarchy that mirrors your org, with a reviewer between what the system notices and what becomes shared knowledge.
Act
Do the work, under a policy that holds. Build, orchestrate, register and monitor every agent, on every cloud, from one control plane.
Assure
Answer for every one of them. Scope-based access control and evidence across all four layers, in whichever perimeter your regulator demands.
GOVERNANCE
SENSE + EVALUATE + REMEMBER + ACT + ASSURE
Enterprise General Intelligence
EGI is not one giant model. It is an enterprise that continuously understands its own business, reasons across its own context, executes its own work, learns from what happened, and adapts how it operates, without a transformation programme every time the world moves.
EGIThe loop thatcompounds.
[01 **Understand**
Capture signals & business context
Pulze](/content/products/pulze/index.html) [02 **Reason**
Reason across data, goals & constraints
Axon](/content/products/axon/index.html) [03 **Act**
Execute through agents & real systems
Cortex](/content/products/cortex/index.html) [05 **Learn**
Capture outcomes & improve continuously
Synapse](/content/products/synapse/index.html)
04
Outcome
Drive measurable business outcomes
Business outcomes
Revenue ↑ Increase top-line growth
Cost ↓ Improve efficiency & reduce spend
Speed ↑ Accelerate decision & execution
Risk ↓ Strengthen control & compliance
Every outcome makes the enterprise smarter.
Four components. Deploy one, or compose the stack.
SERAA is not a monolith you buy whole. Each component is a product in its own right, with its own buyer, its own business case and its own deployment path, and a shared context interface, so the ones you add later compound instead of collide. Start where the pain is. Most enterprises start with one.
Sense · SignalPulzeEvaluate · Data & reasoningAxonRemember · MemorySynapseAct · Agent operating systemCortex
Signal layer · deploys standalone
SERAA Pulze
What your best rep knows, everywhere.
The tribal knowledge trapped in meetings and market noise, captured and put to work. Two editions on one architecture, SalesPulze for revenue teams, MarketPulze for brand and competitor sentiment. Run it on its own for functional ROI, or pipe its signal straight into Axon and Synapse.
Components — SERAA Pulze
SalesPulzeRevenue teams
MarketPulzeBrand & competitive
Signal captureMeetings · field · market feeds
RunsStandalone
01
Multi-source ingestion
Ingests meetings, social feeds, industry publications and filings into one signal layer, alongside the systems you already run.
02
Evidence-linked insight
Confidence-scored, evidence-linked output rather than a black box, every insight traces back to its source.
03
Real-time coaching
Live coaching signal generated from every customer conversation, surfaced back to the rep in the moment.
04
Feeds the loop
Signal is written to SERAA Synapse and made available to SERAA Axon automatically, no manual hand-off.
Real-time Coaching signal per call
4 pillars Sentiment, in the Market edition
Fastest Route to visible ROI in the portfolio
Auto-fed Signal written straight to Synapse
Data & reasoning layer · deploys standalone
SERAA Axon
Ask your company a question. Get your company’s answer.
The enterprise reasoning layer. Axon connects your ERPs, CRMs, data lakes, documents and IoT streams into one semantic layer, then answers the questions leadership actually asks — in real time, with full explainability. Not a BI tool. It reasons.
Components — SERAA Axon
Intelligent ArchitectModel by conversation
Universal Connectivity100+ connectors
Master Data SovereigntyGolden Records
Reasoning & Rule FactoryHybrid retrieval
Command CenterAsk in plain language
RunsStandalone
01
Multimodal connectivity
100+ connectors to SAP, Oracle, Salesforce, lakes, IoT and unstructured archives — fused into one semantic layer.
02
Composable reasoning chain
SQL, vector and graph combined in a single chain — defined in natural language, verified by admins, run with deterministic guardrails.
03
Master data sovereignty
Agent-governed MDM applies rules written in plain English and builds continuously improving Golden Records. Clean data isn't a prerequisite to start.
04
Contract & document intelligence
Semantically scans thousands of contracts and regulatory texts in seconds, surfacing obligations keyword search misses.
05
Explainability & compliance
A complete reasoned audit trail at every decision node. No unverified AI action is taken. Built for regulated industries.
50–80% Less time from data to decision †
80% Less pipeline engineering effort †
~2 min To activate a hybrid reasoning rule
4 wks Average to live enterprise intelligence †
Memory layer · alpha · deploys standalone
SERAA Synapse
Nothing becomes company knowledge until a person says so.
Hierarchical memory infrastructure for enterprise AI. A flat vector store is not an enterprise memory — enterprises aren’t flat. Synapse gives every tenant a Layer hierarchy that mirrors their real structure, and puts a human between "the AI noticed something" and "this is now shared knowledge."
Components — SERAA Synapse
Layer hierarchyTenant → Project → Memory
Context SDKPython & TypeScript
Governance queueHuman approval
Knowledge Mind MapClick to explore
RunsStandalone · alpha
01
A hierarchy, not an index
Tenant-defined Layers — Tenant → Project → Enterprise Memory → Layers. Retrieval is scoped to a Layer path, so one branch's local exception can't leak into another region's answers.
02
Static plus adaptive
Static Layers hold documents you upload, indexed immediately. Adaptive Layers mine patterns from real conversations that recur across enough distinct people and sessions.
03
The learning loop
Observe → Detect → Review → Promote → Record. A reviewer sees the exact text that would be written, never a paraphrase, and can edit, approve, reject or later demote it.
04
A platform, not a library
Self-service portal, a playground with a full Layer trace, a governance queue, a click-to-explore Mind Map, and an audit trail scoped to a single Enterprise Memory.
11 Industry templates shipped
2 SDKs Python and TypeScript, live today
1 human Reviews every promotion before it ships
8 surfaces Portal, playground, queue, mind map…
Agent runtime · deploys standalone
SERAA Cortex
Every agent you run. One screen. One switch.
The operating system for the enterprise agent lifecycle. Four modules carry an agent from first build to live production, each handing off to the next — Agent Work Bench, Registry and Control Tower are also available standalone, so you can govern an agent estate you built elsewhere.
Components — SERAA Cortex
Agent Work BenchNo-code & pro-code
Multi-Agent OrchestrationVisual canvas
Agent RegistryCatalog & promotion
Agent Control TowerCost · guardrails · logs
Agent Test BenchEvaluation · beta
RunsStandalone
01
Agent Work Bench — build
No-code and pro-code agents in one interface. Model Hub with 100+ LLMs, an MCP Hub for tools, and a playground for model-by-model validation before deployment.
02
Multi-Agent Orchestration
Visual drag-and-drop canvas for sequential chains and parallel branches. A2A protocol support so third-party agents compose natively, with a different model per stage.
03
Agent Registry — register
Universal catalogue, auto-discovered from Gemini Enterprise, Azure AI Foundry, Bedrock and AgentBricks. Dev → QA → Staging → Production with gates, deploying to GKE, AKS, EKS or Agent Engine.
04
Agent Test Bench beta
Builds a high-fidelity simulation from your own historical logs and stress-tests the agent before a single real request reaches it — scored on faithfulness and context precision.
05
Agent Control Tower — monitor
Cost attribution by agent, model and provider. A full audit log of every LLM call. Content and PII guardrails at runtime, plus an instant kill switch for any agent, on any cloud.
70% Faster time-to-market for new agents †
40–60% LLM cost reduction via governed routing †
4 clouds Discovered into one catalogue
Zero Model or cloud lock-in
How this composes
Every component ships with its own licence, its own scopes and its own deployment plan, so procurement buys one thing and one team owns it. Nothing forces a second purchase. What changes when you add the next one is that they stop guessing at each other, Pulze’s signal lands in Synapse, Axon reasons over the Golden Records beneath it, Cortex’s agents read the same memory instead of starting cold. Sequence it to your business case, not to ours.
Governance is the architecture, not a module.
Scope-Based Access Control organises every resource around three nested scopes that mirror how enterprises already operate. Assets flow up. Infrastructure flows down.
Two resource categories, two opposite flowsThe single rule that lets thousands of builders move without governance losing sight of any of them
ASSETS FLOW UP ▲agents · knowledge bases · tools▼ INFRASTRUCTURE FLOWS DOWNmodels · environments · providersSYSTEMEnterprise standards, approved models, policy14 modelsORGANIZATIONA business unit, inside System guardrails5 modelsPROJECTOne use case. Never wider.2 modelsvisible toevery scopeabove itnever belowa curatedsubset ateach levelnever widerOne account can be Viewer at System, Admin in an Organization, Contributor on a Project.
Governance teams always see everything built beneath them. Teams below can never depend on assets being curated above them, or reach for capability their parent has not granted.
ISO 42001 certifiedRBAC & ABACEntra ID & GCP IAM SSOGDPR & HIPAA policyEU AI Act alignedPII detection & redactionPer-customer VPC sovereignty
Four advantages, one per layer.
Not one idea stretched across four products, each layer earns its place against the tools that already claim to do this.
01 · Sense
Signal nobody else can reach
What was said in the meeting and what the market is doing right now never enters a system of record. Pulze captures it and reasons over it alongside your ERP data.
vs. CRM & BI, they can only reason over what someone remembered to type in.
02 · Evaluate
Three retrieval methods, one chain
SQL for structured precision, vector for document meaning, graph for relationships, composed in a single reasoning chain with the audit trail attached.
vs. most tools, they use exactly one method.
03 · Remember
Memory with a human in the loop
A Layer hierarchy that matches your org, adaptive learning from real usage, and a reviewer who sees the exact text before it becomes shared knowledge.
vs. a vector database; flat index, no promotion path, no review.
04 · Act
Governance that crosses clouds
One catalogue, one policy engine and one cost view across agents on GKE, AKS, EKS and Agent Engine, discovered from four vendor platforms, whoever built them.
vs. hyperscalers, each stops at its own boundary.
Pre-built for your vertical.
Generic analytics doesn’t understand your supply chain. Pre-built intelligence models and domain ontologies connect the systems you already run.
BFSI
The wealth back office, run by governed agents
- Onboarding and KYC documents triaged before a reviewer opens them
- Registry and depository submissions pre-validated to stop next-day rework
- Settlement and payout checks in parallel, agent proposes, human approves
70%
Fewer onboarding rejections †
5×
Faster daily reconciliation †
Manufacturing
Predictive operations, plant to supply chain
- Multi-tier supplier reliability and risk detection
- OEE optimisation with cross-system root cause analysis
- Predictive maintenance, cross-analysed with history
23%
Less unplanned downtime †
4×
Faster risk identification †
Healthcare
Clinical and operational intelligence, unified
- Patient journey across clinical and operational touchpoints
- Readmission risk scoring with cross-system context
- Revenue cycle optimisation and billing anomaly detection
19%
Fewer 30-day readmissions †
60%
Less manual compliance work †
Insights
Insights that help you lead the AI shift.
The executives transforming their organizations with Agentic AI are asking harder questions and demanding better answers. These are the reads that help you get there faster.
Whitepaper
Data Observability: The Backbone of Reliable AI Systems
Discover how building a strong foundation for data observability helps identify issues early, maintain data integrity, and create AI systems that you can truly trust.
Control Tower 5 min read From Chaos to Control: How an AI Agent Control Tower Protects Enterprises from Agent Anarchy AI Strategy 6 min read Enterprise AI Adoption: A Six-Phase Roadmap Built Around Business Outcomes Risk & Compliance 4 min read How CROs and CCOs Can Get Ahead of the Autonomous AI Agent Governance Challenge
Answer anything. Account for everything.
Bring us one question your data can't currently answer, or one agent estate nobody can currently see. We'll tell you which of the five layers you actually need first, and which you don't.