Valtara synthesizes eight layers of institutional-grade data into a calibrated, traceable market brief for XAU/USD — consumable by human trader or autonomous agent.
Powered by institutional-grade data & AI providers
Valtara's north star is to make the analytical depth that previously required a Bloomberg Terminal, a quant team, and a Reuters feed accessible, transparent, and composable — for retail traders, developers, and small institutions alike.
Stop stitching dashboards, CSV exports, and three news terminals together. Valtara ingests primary macro, positioning, and market-microstructure streams into a single synchronized pipeline — so every signal ships with a traceable source.
Each layer is independently testable and replaceable — yet flows upward into a unified, auditable analytical output.
Acquires, cleans, and time-synchronizes primary data streams into a single coherent pipeline. Every datapoint carries its source identifier and timestamp, enabling full downstream auditability.
Transforms raw streams into structured analytical constructs — bias score, limit order zones, active setups, scenario paths, and deterministic execution signals with explicit invalidation levels.
Eight specialist agents — each accountable for one analytical domain — run in parallel and feed a single Opus-tier Master that returns a calibrated probability distribution with disagreement entropy for conviction scoring.
Symmetric consumption surface — an interactive dashboard for humans, a REST API and Model Context Protocol server for autonomous agents. Event-driven, WebSocket-pushed, and fully audited in append-only JSONL.
What separates Valtara from indicator stacks and black-box AI — purpose-built for depth, calibration, and transparency.
Every bias decision and trade setup is snapshotted into a decisions store, then retrospectively labeled against price realization — building a corpus of lived experience the Master Synthesis can retrieve against.
Content-hash deduplication, cooldown protection, and WebSocket push keep the engine responsive without wasteful recomputes. Eight specialist agents run in parallel, a Master Synthesis fires only when signal actually shifts.
Brier scores per component feed weekly weight updates — the blend of macro, positioning, flow, and risk-off signals tunes itself toward whichever layer is currently predictive, with bounded learning rate and audit trail.
Symmetric endpoints for humans and agents. Install Valtara as a skill inside Hermes, OpenClaw, or Claude Computer Use — your autonomous executor gets domain intelligence without rebuilding the pipeline.
Every score, tilt, and narrative line is traceable to its primary source — FRED series id, COT report date, SMC anchor, news timestamp. No black box, no unaccountable conviction.
Valtara is not a competitor to autonomous agent frameworks — it is their domain-specific cognitive layer. The same intelligence feeds three consumption modes, cleanly separated.
Open the Valtara dashboard, read the bias and scenario brief, pull the trigger yourself on MT5 or your broker of choice. Zero dependency on external agents.
Valtara pushes calibrated setups to your MT5 Expert Advisor or custom webhook endpoint. Semi-automated execution with human oversight — the pragmatic middle ground.
Install Valtara as a skill inside Hermes, OpenClaw, or Claude Computer Use. Your agent consumes bias, scenarios, and setups through MCP — then reasons and executes on its own.
Hermes and OpenClaw excel at generic planning, tool use, and execution. But gold market intelligence — eight-layer data fusion, calibrated probability, and traceable reasoning — doesn't emerge spontaneously from a ReAct loop. Valtara plugs the gap.
Each phase deepens capability without altering the product's core positioning — analytical pipeline, then memory-augmented advisor, then composable intelligence infrastructure.
Current focus · v5.7.5 → v6.x
Adds episodic and semantic memory: decisions store, outcomes store, embeddings-based analog retrieval, pattern library clustering, and Bayesian weight recalibration from Brier scores.
Formalizes third-party consumption
API versioning, authentication and rate limiting per tier, formal Model Context Protocol server wrapper, OpenAPI schema, webhook event push, and a developer documentation portal with sandbox credentials.
Distribution & partnerships
Publish skill packages on ClawHub and Hermes Skill Marketplace, revenue-share partnerships with futures brokers, white-label programs for regional prop firms, and disciplined asset expansion driven by empirical demand.
From curious retail explorer to agent integrator to institutional desk — one brain, four access levels.
For retail traders exploring institutional-grade analysis for the first time.
For active retail traders and independent prop traders running daily sessions.
For agent integrators, systematic traders, and developers building autonomous bots.
For prop trading firms, family offices, and small hedge funds needing SLA-backed delivery.
Kurs konversi ≈ Rp 16.100 / USD (indikatif). Valtara adalah advisory infrastructure dan bukan auto-trader; pengguna bertanggung jawab penuh atas setiap keputusan eksekusi.