Trading & Capital Markets
Forex Technical Analysis API
Your traders want a reason to take the next trade. This is the research layer that gives them one — under your brand, inside your platform, without you hiring a technical-analysis desk.
- Forex and CFD brokers
- Trading terminals
- Prop firms
- Charting platforms
What your customers would see
example interfaceMockupIllustrative mockup of the interface we would build. Figures shown are examples, not results from a live deployment.
The problem this solves
Almost every retail broker reaches the same conclusion eventually: traders who see actionable research log in more often and trade more consistently than traders who see a bare price chart. The usual response is to license a module from one of the two or three incumbent research vendors, accept their branding constraints and their per-seat pricing, and move on.
That works, but it leaves you renting a core part of your product experience. You cannot change the instrument coverage, you cannot tune the signal frequency to your audience, and you cannot extend the module into the rest of your platform. When the vendor raises prices at renewal, your options are limited.
The alternative is to own the layer. A pattern and level engine is a well-understood piece of engineering — the difficulty is not the geometry, it is doing it consistently across hundreds of instruments and timeframes, keeping it fast enough to serve inside a live chart, and being honest about how the patterns have actually performed historically rather than asserting that they work.
Who buys this
Forex and CFD brokers, Trading terminals, Prop firms, Charting platforms
What the API returns
What comes back
- Detected chart patterns with completion state and target levels
- Support and resistance zones ranked by the number of touches and recency
- Breakout and retest events as they complete, with the invalidation level
- Trend classification per instrument and timeframe
- Volatility context so a setup is read against current conditions
- Historical hit rate for each pattern type on that instrument and timeframe
- Chart overlay geometry your front end can draw directly
- A plain-language summary line suitable for display to end users
Endpoints
| Method | Path | Returns |
|---|---|---|
| GET | /v1/analysis/{symbol} | Current patterns, levels and trend for one instrument |
| GET | /v1/analysis/{symbol}/levels | Support and resistance zones only |
| GET | /v1/signals | Setups completing across your whole instrument universe |
| POST | /v1/scan | Scan a symbol list against pattern and quality filters |
| GET | /v1/patterns/{pattern}/performance | Historical performance of a pattern type |
| WS | /v1/stream | Push new completions and invalidations as they happen |
Request and response
illustrativeRequest
{
"symbol": "EURUSD",
"timeframe": "H4",
"include": ["patterns", "levels", "trend", "overlay"],
"min_quality": 60
}Response
{
"symbol": "EURUSD",
"timeframe": "H4",
"as_of": "2026-10-21T14:00:00Z",
"trend": { "direction": "up", "strength": 0.61, "since": "2026-10-09" },
"volatility": { "atr_pips": 48.2, "percentile": 0.37, "regime": "normal" },
"patterns": [
{
"type": "ascending_triangle",
"state": "completed",
"completed_at": "2026-10-21T08:00:00Z",
"quality": 74,
"target": 1.0982,
"invalidation": 1.0834,
"historical": { "sample": 412, "target_hit_rate": 0.58 }
}
],
"levels": [
{ "price": 1.0840, "type": "support", "touches": 5, "strength": 0.82 },
{ "price": 1.0975, "type": "resistance", "touches": 3, "strength": 0.64 }
],
"summary": "Ascending triangle completed on H4; resistance at 1.0975."
}Where the data comes from
| Your own price feed | The OHLC history you already receive from your liquidity provider or market data vendor |
| Licensed market data | Where you need instruments outside your own feed, under a licence that permits derived analytics |
| Tick or minute history | Needed to build the historical archive the performance statistics are computed from |
| Economic calendar data | So setups can be suppressed or flagged around scheduled high-impact releases |
| Session and holiday calendars | Correct handling of thin liquidity periods, rollovers and market closures |
| Your historical trade data | Optional, and only with your agreement — lets the quality score be tuned to how your own users actually trade |
The intelligence layer
The difference between a demo and a service is mostly in this section. These are the parts that keep the answer trustworthy once real traffic is hitting it.
- Geometric pattern detection with tolerance bands rather than exact-match rules, so real-world noise does not suppress valid formations
- Level clustering that merges nearby touches into zones instead of reporting dozens of near-identical price lines
- Trend classification from slope, structure and moving-average relationships combined, not a single indicator
- A quality score trained on how each pattern type has historically resolved on that specific instrument and timeframe
- Volatility regime detection so the same formation is scored differently in calm and disorderly markets
- Walk-forward validation on held-out history — never an in-sample fit presented as a result
- Explicit suppression windows around scheduled economic releases
- Monitoring for detection drift as market structure changes over the years
What it changes for the business
Session frequency
Research that updates through the day gives traders a reason to open the platform when they are not already in a position.
Lower research cost
You stop paying per-seat licensing on a module you could own, which changes the economics as your user base grows.
Product differentiation
Coverage, signal frequency and presentation become yours to tune rather than a vendor's roadmap.
Retention signal
Pattern alerts give you a legitimate reason to re-engage dormant accounts without pushing them to trade.
How it fits into your product
How it embeds
- Fully white-label: your brand, your domain, no MLPivot marks anywhere in the output
- Chart overlay geometry returned as coordinates your existing charting library can draw
- Embeddable widgets if you would rather not build the front end yourself
- WebSocket stream for live completions, REST for on-demand lookups
- Webhooks into your notification system for push alerts and email digests
- Per-user entitlements so research can be gated by account tier
Included in every build
- Authentication, scoped API keys and per-customer rate limiting
- Input validation with predictable, documented error responses
- Versioned endpoints so your integration never breaks without notice
- Request and response logging for audit and dispute resolution
- Latency, error-rate and usage monitoring with alerting
- OpenAPI specification, sandbox environment and client examples
- Backups, failover design and a documented recovery procedure
- An agreed support arrangement once the service is live
How we would build it
about 12 weeksDiscovery and data review
Weeks 1–2
We agree the exact question the API answers, review the sources you already hold, check what has to be licensed, and write down the response contract your developers will code against.
Architecture and prototype
Weeks 3–4
You get a written architecture plus a working endpoint on real data — narrow, but genuinely callable — so integration can be tested against something concrete rather than a document.
Production build
Weeks 5–10
Pipelines, models, storage, authentication, rate limiting, logging, tests and documentation. Security and observability are part of this phase, not a later one.
Integration and handover
Weeks 11–12
We support your engineers through their integration, run load tests at your expected volume, and agree how the service is monitored and supported once it is live.
Commercial models
There is no fixed price list, because the cost is driven by data complexity, integration count, model requirements, request volume and the support level you need. Scope is agreed in writing before development starts.
Fixed-scope prototype
A defined slice of the service, built and priced as one piece of work. The usual first step when the business case needs proving internally.
Fixed-price build
An agreed scope against a written architecture, delivered for an agreed price. Best when the requirements are already clear.
Build then retainer
We build the service, then operate and improve it under a monthly agreement covering monitoring, updates and model maintenance.
White-label product
The service runs under your brand, your domain and your pricing, with MLPivot invisible to your customers.
Questions buyers ask
Can we present this as our own research?
Yes. White-label is the normal arrangement for this build — your brand, your domain, no attribution requirement. We would ask that any performance figures shown to end users reflect what the validation actually measured.
How do you avoid producing financial advice?
The API returns observations and statistics, not recommendations. Patterns and levels are facts about the chart; historical hit rates are measurements. How you present them, what disclaimers you carry and whether your jurisdiction treats that as advice is a question for your compliance team, and we will build to whatever constraints they set.
What instrument coverage is realistic?
Whatever your price feed covers. FX majors, minors and crosses, indices, commodities and major equities are all routine. The constraint is data licensing rather than engineering.
How fast is it?
Pattern state is recomputed per bar close, so H4 analysis updates every four hours while M5 updates every five minutes. Cached responses typically return in 20–60ms, which is fast enough to render inside a live chart.
Will you tell us if a pattern type does not work?
Yes, and we would rather do that during the prototype than after launch. If a formation shows no edge on your instruments, the honest options are to drop it, present it as a neutral observation, or keep it with the real statistics attached. We will not manufacture a hit rate.
Related blueprints
Economic Event Intelligence API
An economic calendar with impact scoring, surprise measurement and the historical reaction of each instrument to each release.
Market Sentiment & Positioning API
Aggregated sentiment and positioning estimates by instrument, delivered as a feed your platform can display or trade against.
Trading Journal Analytics API
Behavioural analysis of closed trades that tells a trader what is actually costing them money, as a retention feature inside your platform.
Want this built for your platform?
Tell us what your product does today and what you want another system to be able to ask it. We will come back with an approach, a scope and a price.